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AlexMaclean/sentence-compression
https://huggingface.co/AlexMaclean/sentence-compression
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexMaclean/sentence-compression ### Model URL : https://huggingface.co/AlexMaclean/sentence-compression ### Model Description : This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AlexN/xls-r-300m-fr-0
https://huggingface.co/AlexN/xls-r-300m-fr-0
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexN/xls-r-300m-fr-0 ### Model URL : https://huggingface.co/AlexN/xls-r-300m-fr-0 ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AlexN/xls-r-300m-fr
https://huggingface.co/AlexN/xls-r-300m-fr
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset. More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexN/xls-r-300m-fr ### Model URL : https://huggingface.co/AlexN/xls-r-300m-fr ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset. More information needed More information needed More information needed The following hyperparameters were used during training:
AlexN/xls-r-300m-pt
https://huggingface.co/AlexN/xls-r-300m-pt
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - PT dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexN/xls-r-300m-pt ### Model URL : https://huggingface.co/AlexN/xls-r-300m-pt ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - PT dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AlexaMerens/Owl
https://huggingface.co/AlexaMerens/Owl
null
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexaMerens/Owl ### Model URL : https://huggingface.co/AlexaMerens/Owl ### Model Description :
AlexaRyck/KEITH
https://huggingface.co/AlexaRyck/KEITH
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexaRyck/KEITH ### Model URL : https://huggingface.co/AlexaRyck/KEITH ### Model Description : No model card New: Create and edit this model card directly on the website!
Alexander-Learn/bert-finetuned-ner-accelerate
https://huggingface.co/Alexander-Learn/bert-finetuned-ner-accelerate
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alexander-Learn/bert-finetuned-ner-accelerate ### Model URL : https://huggingface.co/Alexander-Learn/bert-finetuned-ner-accelerate ### Model Description : No model card New: Create and edit this model card directly on the website!
Alexander-Learn/bert-finetuned-ner
https://huggingface.co/Alexander-Learn/bert-finetuned-ner
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alexander-Learn/bert-finetuned-ner ### Model URL : https://huggingface.co/Alexander-Learn/bert-finetuned-ner ### Model Description : No model card New: Create and edit this model card directly on the website!
Alexander-Learn/bert-finetuned-squad-accelerate
https://huggingface.co/Alexander-Learn/bert-finetuned-squad-accelerate
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alexander-Learn/bert-finetuned-squad-accelerate ### Model URL : https://huggingface.co/Alexander-Learn/bert-finetuned-squad-accelerate ### Model Description : No model card New: Create and edit this model card directly on the website!
Alexander-Learn/bert-finetuned-squad
https://huggingface.co/Alexander-Learn/bert-finetuned-squad
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alexander-Learn/bert-finetuned-squad ### Model URL : https://huggingface.co/Alexander-Learn/bert-finetuned-squad ### Model Description : No model card New: Create and edit this model card directly on the website!
Alexandru/creative_copilot
https://huggingface.co/Alexandru/creative_copilot
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alexandru/creative_copilot ### Model URL : https://huggingface.co/Alexandru/creative_copilot ### Model Description : No model card New: Create and edit this model card directly on the website!
AlexeyIgnatov/albert-xlarge-v2-squad-v2
https://huggingface.co/AlexeyIgnatov/albert-xlarge-v2-squad-v2
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexeyIgnatov/albert-xlarge-v2-squad-v2 ### Model URL : https://huggingface.co/AlexeyIgnatov/albert-xlarge-v2-squad-v2 ### Model Description : No model card New: Create and edit this model card directly on the website!
AlexeyYazev/my-awesome-model
https://huggingface.co/AlexeyYazev/my-awesome-model
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlexeyYazev/my-awesome-model ### Model URL : https://huggingface.co/AlexeyYazev/my-awesome-model ### Model Description : No model card New: Create and edit this model card directly on the website!
Alfia/anekdotes
https://huggingface.co/Alfia/anekdotes
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alfia/anekdotes ### Model URL : https://huggingface.co/Alfia/anekdotes ### Model Description : No model card New: Create and edit this model card directly on the website!
AliPotter24/a
https://huggingface.co/AliPotter24/a
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AliPotter24/a ### Model URL : https://huggingface.co/AliPotter24/a ### Model Description : No model card New: Create and edit this model card directly on the website!
Alicanke/Wyau
https://huggingface.co/Alicanke/Wyau
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alicanke/Wyau ### Model URL : https://huggingface.co/Alicanke/Wyau ### Model Description : No model card New: Create and edit this model card directly on the website!
Alifarsi/t5-small-finetuned-xsum
https://huggingface.co/Alifarsi/t5-small-finetuned-xsum
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alifarsi/t5-small-finetuned-xsum ### Model URL : https://huggingface.co/Alifarsi/t5-small-finetuned-xsum ### Model Description : No model card New: Create and edit this model card directly on the website!
Aliraza47/BERT
https://huggingface.co/Aliraza47/BERT
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Aliraza47/BERT ### Model URL : https://huggingface.co/Aliraza47/BERT ### Model Description : No model card New: Create and edit this model card directly on the website!
Alireza-rw/testbot
https://huggingface.co/Alireza-rw/testbot
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza-rw/testbot ### Model URL : https://huggingface.co/Alireza-rw/testbot ### Model Description : No model card New: Create and edit this model card directly on the website!
Alireza1044/albert-base-v2-cola
https://huggingface.co/Alireza1044/albert-base-v2-cola
This model is a fine-tuned version of albert-base-v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-cola ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-cola ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-mnli
https://huggingface.co/Alireza1044/albert-base-v2-mnli
This model is a fine-tuned version of albert-base-v2 on the GLUE MNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-mnli ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-mnli ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE MNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-mrpc
https://huggingface.co/Alireza1044/albert-base-v2-mrpc
This model is a fine-tuned version of albert-base-v2 on the GLUE MRPC dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-mrpc ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-mrpc ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE MRPC dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-qnli
https://huggingface.co/Alireza1044/albert-base-v2-qnli
This model is a fine-tuned version of albert-base-v2 on the GLUE QNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-qnli ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-qnli ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE QNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-qqp
https://huggingface.co/Alireza1044/albert-base-v2-qqp
This model is a fine-tuned version of albert-base-v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-qqp ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-qqp ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-rte
https://huggingface.co/Alireza1044/albert-base-v2-rte
This model is a fine-tuned version of albert-base-v2 on the GLUE RTE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-rte ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-rte ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE RTE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-sst2
https://huggingface.co/Alireza1044/albert-base-v2-sst2
This model is a fine-tuned version of albert-base-v2 on the GLUE SST2 dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-sst2 ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-sst2 ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE SST2 dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-stsb
https://huggingface.co/Alireza1044/albert-base-v2-stsb
This model is a fine-tuned version of albert-base-v2 on the GLUE STSB dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-stsb ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-stsb ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE STSB dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/albert-base-v2-wnli
https://huggingface.co/Alireza1044/albert-base-v2-wnli
This model is a fine-tuned version of albert-base-v2 on the GLUE WNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/albert-base-v2-wnli ### Model URL : https://huggingface.co/Alireza1044/albert-base-v2-wnli ### Model Description : This model is a fine-tuned version of albert-base-v2 on the GLUE WNLI dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alireza1044/bert_classification_lm
https://huggingface.co/Alireza1044/bert_classification_lm
A simple model trained on dialogues of characters in NBC series, The Office. The model can do a binary classification between Michael Scott and Dwight Shrute's dialogues.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/bert_classification_lm ### Model URL : https://huggingface.co/Alireza1044/bert_classification_lm ### Model Description : A simple model trained on dialogues of characters in NBC series, The Office. The model can do a binary classification between Michael Scott and Dwight Shrute's dialogues.
Alireza1044/dwight_bert_lm
https://huggingface.co/Alireza1044/dwight_bert_lm
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/dwight_bert_lm ### Model URL : https://huggingface.co/Alireza1044/dwight_bert_lm ### Model Description : No model card New: Create and edit this model card directly on the website!
Alireza1044/michael_bert_lm
https://huggingface.co/Alireza1044/michael_bert_lm
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alireza1044/michael_bert_lm ### Model URL : https://huggingface.co/Alireza1044/michael_bert_lm ### Model Description : No model card New: Create and edit this model card directly on the website!
AlirezaBaneshi/testPersianQA
https://huggingface.co/AlirezaBaneshi/testPersianQA
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AlirezaBaneshi/testPersianQA ### Model URL : https://huggingface.co/AlirezaBaneshi/testPersianQA ### Model Description : No model card New: Create and edit this model card directly on the website!
Aliskin/xlm-roberta-base-finetuned-marc
https://huggingface.co/Aliskin/xlm-roberta-base-finetuned-marc
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Aliskin/xlm-roberta-base-finetuned-marc ### Model URL : https://huggingface.co/Aliskin/xlm-roberta-base-finetuned-marc ### Model Description : No model card New: Create and edit this model card directly on the website!
Aliyyu/Keren
https://huggingface.co/Aliyyu/Keren
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Aliyyu/Keren ### Model URL : https://huggingface.co/Aliyyu/Keren ### Model Description : No model card New: Create and edit this model card directly on the website!
AllwynJ/HarryBoy
https://huggingface.co/AllwynJ/HarryBoy
#HarryBoy
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AllwynJ/HarryBoy ### Model URL : https://huggingface.co/AllwynJ/HarryBoy ### Model Description : #HarryBoy
Allybaby21/Allysai
https://huggingface.co/Allybaby21/Allysai
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Allybaby21/Allysai ### Model URL : https://huggingface.co/Allybaby21/Allysai ### Model Description : No model card New: Create and edit this model card directly on the website!
Aloka/mbart50-ft-si-en
https://huggingface.co/Aloka/mbart50-ft-si-en
This model was trained from scratch on an unkown dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Aloka/mbart50-ft-si-en ### Model URL : https://huggingface.co/Aloka/mbart50-ft-si-en ### Model Description : This model was trained from scratch on an unkown dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Alstractor/distilbert-base-uncased-finetuned-cola
https://huggingface.co/Alstractor/distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alstractor/distilbert-base-uncased-finetuned-cola ### Model URL : https://huggingface.co/Alstractor/distilbert-base-uncased-finetuned-cola ### Model Description : This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Altidore/DuggFace
https://huggingface.co/Altidore/DuggFace
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Altidore/DuggFace ### Model URL : https://huggingface.co/Altidore/DuggFace ### Model Description : No model card New: Create and edit this model card directly on the website!
Alvenir/wav2vec2-base-da
https://huggingface.co/Alvenir/wav2vec2-base-da
This wav2vec2-base model has been pretrained on ~1300 hours of danish speech data. The pretraining data consists of podcasts and audiobooks and is unfortunately not public available. However, we were allowed to distribute the pretrained model. This model was pretrained on 16kHz sampled speech audio. When using the model, make sure to use speech audio sampled at 16kHz. The pre-training was done using the fairseq library in January 2021. It needs to be fine-tuned to perform speech recognition. In order to finetune the model to speech recognition, you can draw inspiration from this notebook tutorial or this blog post tutorial.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Alvenir/wav2vec2-base-da ### Model URL : https://huggingface.co/Alvenir/wav2vec2-base-da ### Model Description : This wav2vec2-base model has been pretrained on ~1300 hours of danish speech data. The pretraining data consists of podcasts and audiobooks and is unfortunately not public available. However, we were allowed to distribute the pretrained model. This model was pretrained on 16kHz sampled speech audio. When using the model, make sure to use speech audio sampled at 16kHz. The pre-training was done using the fairseq library in January 2021. It needs to be fine-tuned to perform speech recognition. In order to finetune the model to speech recognition, you can draw inspiration from this notebook tutorial or this blog post tutorial.
Amalq/distilroberta-base-finetuned-MentalHealth
https://huggingface.co/Amalq/distilroberta-base-finetuned-MentalHealth
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amalq/distilroberta-base-finetuned-MentalHealth ### Model URL : https://huggingface.co/Amalq/distilroberta-base-finetuned-MentalHealth ### Model Description : No model card New: Create and edit this model card directly on the website!
Amalq/distilroberta-base-finetuned-anxiety-depression
https://huggingface.co/Amalq/distilroberta-base-finetuned-anxiety-depression
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amalq/distilroberta-base-finetuned-anxiety-depression ### Model URL : https://huggingface.co/Amalq/distilroberta-base-finetuned-anxiety-depression ### Model Description : No model card New: Create and edit this model card directly on the website!
Amalq/roberta-base-finetuned-schizophreniaReddit2
https://huggingface.co/Amalq/roberta-base-finetuned-schizophreniaReddit2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amalq/roberta-base-finetuned-schizophreniaReddit2 ### Model URL : https://huggingface.co/Amalq/roberta-base-finetuned-schizophreniaReddit2 ### Model Description : This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AmanPriyanshu/DistilBert-Sentiment-Analysis
https://huggingface.co/AmanPriyanshu/DistilBert-Sentiment-Analysis
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AmanPriyanshu/DistilBert-Sentiment-Analysis ### Model URL : https://huggingface.co/AmanPriyanshu/DistilBert-Sentiment-Analysis ### Model Description : No model card New: Create and edit this model card directly on the website!
AmazonScience/qanlu
https://huggingface.co/AmazonScience/qanlu
Question Answering NLU (QANLU) is an approach that maps the NLU task into question answering, leveraging pre-trained question-answering models to perform well on few-shot settings. Instead of training an intent classifier or a slot tagger, for example, we can ask the model intent- and slot-related questions in natural language: Note the "Yes. No. " prepended in the context. Those are to allow the model to answer intent-related questions (e.g. "Is the user looking for a restaurant?"). Thus, by asking questions for each intent and slot in natural language, we can effectively construct an NLU hypothesis. For more details, please read the paper: Language model is all you need: Natural language understanding as question answering. Instructions for how to train and evaluate a QANLU model, as well as the necessary code for ATIS are in the Amazon Science repository. This model has been fine-tuned on ATIS (English) and is intended to demonstrate the power of this approach. For other domains or tasks, it should be further fine-tuned on relevant data. If you use this work, please cite: This library is licensed under the CC BY NC License.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AmazonScience/qanlu ### Model URL : https://huggingface.co/AmazonScience/qanlu ### Model Description : Question Answering NLU (QANLU) is an approach that maps the NLU task into question answering, leveraging pre-trained question-answering models to perform well on few-shot settings. Instead of training an intent classifier or a slot tagger, for example, we can ask the model intent- and slot-related questions in natural language: Note the "Yes. No. " prepended in the context. Those are to allow the model to answer intent-related questions (e.g. "Is the user looking for a restaurant?"). Thus, by asking questions for each intent and slot in natural language, we can effectively construct an NLU hypothesis. For more details, please read the paper: Language model is all you need: Natural language understanding as question answering. Instructions for how to train and evaluate a QANLU model, as well as the necessary code for ATIS are in the Amazon Science repository. This model has been fine-tuned on ATIS (English) and is intended to demonstrate the power of this approach. For other domains or tasks, it should be further fine-tuned on relevant data. If you use this work, please cite: This library is licensed under the CC BY NC License.
Amba/wav2vec2-large-xls-r-300m-tr-colab
https://huggingface.co/Amba/wav2vec2-large-xls-r-300m-tr-colab
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Amba/wav2vec2-large-xls-r-300m-turkish-colab
https://huggingface.co/Amba/wav2vec2-large-xls-r-300m-turkish-colab
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amba/wav2vec2-large-xls-r-300m-turkish-colab ### Model URL : https://huggingface.co/Amba/wav2vec2-large-xls-r-300m-turkish-colab ### Model Description : No model card New: Create and edit this model card directly on the website!
aisoftware/Loquela
https://huggingface.co/aisoftware/Loquela
No model card New: Create and edit this model card directly on the website!
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Amir99/toxic
https://huggingface.co/Amir99/toxic
No model card New: Create and edit this model card directly on the website!
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AmirBialer/amirbialer-Classifier
https://huggingface.co/AmirBialer/amirbialer-Classifier
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AmirHussein/test
https://huggingface.co/AmirHussein/test
No model card New: Create and edit this model card directly on the website!
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AmirServi/MyModel
https://huggingface.co/AmirServi/MyModel
No model card New: Create and edit this model card directly on the website!
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Amirosein/distilbert_v1
https://huggingface.co/Amirosein/distilbert_v1
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Amirosein/roberta
https://huggingface.co/Amirosein/roberta
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Amit29/t5-small-finetuned-xsum
https://huggingface.co/Amit29/t5-small-finetuned-xsum
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AmitT/test
https://huggingface.co/AmitT/test
No model card New: Create and edit this model card directly on the website!
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Amitabh/doc-classification
https://huggingface.co/Amitabh/doc-classification
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Amro-Kamal/gpt
https://huggingface.co/Amro-Kamal/gpt
No model card New: Create and edit this model card directly on the website!
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Amrrs/indian-foods
https://huggingface.co/Amrrs/indian-foods
Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for anything by running the demo on Google Colab. Report any issues with the demo at the github repo.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amrrs/indian-foods ### Model URL : https://huggingface.co/Amrrs/indian-foods ### Model Description : Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for anything by running the demo on Google Colab. Report any issues with the demo at the github repo.
Amrrs/south-indian-foods
https://huggingface.co/Amrrs/south-indian-foods
Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for anything by running the demo on Google Colab. Report any issues with the demo at the github repo.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amrrs/south-indian-foods ### Model URL : https://huggingface.co/Amrrs/south-indian-foods ### Model Description : Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for anything by running the demo on Google Colab. Report any issues with the demo at the github repo.
Amrrs/wav2vec2-large-xlsr-53-tamil
https://huggingface.co/Amrrs/wav2vec2-large-xlsr-53-tamil
Fine-tuned facebook/wav2vec2-large-xlsr-53 in Tamil using the Common Voice When using this model, make sure that your speech input is sampled at 16kHz. The model can be used directly (without a language model) as follows: The model can be evaluated as follows on the {language} test data of Common Voice. Test Result: 82.94 % The Common Voice train, validation datasets were used for training. The script used for training can be found here
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Amrrs/wav2vec2-large-xlsr-53-tamil ### Model URL : https://huggingface.co/Amrrs/wav2vec2-large-xlsr-53-tamil ### Model Description : Fine-tuned facebook/wav2vec2-large-xlsr-53 in Tamil using the Common Voice When using this model, make sure that your speech input is sampled at 16kHz. The model can be used directly (without a language model) as follows: The model can be evaluated as follows on the {language} test data of Common Voice. Test Result: 82.94 % The Common Voice train, validation datasets were used for training. The script used for training can be found here
Ana1315/A
https://huggingface.co/Ana1315/A
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Ana1315/ana
https://huggingface.co/Ana1315/ana
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AnaRhisT/bert_sequence_cs_validation
https://huggingface.co/AnaRhisT/bert_sequence_cs_validation
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Analufm/Ana
https://huggingface.co/Analufm/Ana
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Anamika/autonlp-Feedback1-479512837
https://huggingface.co/Anamika/autonlp-Feedback1-479512837
You can use cURL to access this model: Or Python API:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Anamika/autonlp-Feedback1-479512837 ### Model URL : https://huggingface.co/Anamika/autonlp-Feedback1-479512837 ### Model Description : You can use cURL to access this model: Or Python API:
Anamika/autonlp-fa-473312409
https://huggingface.co/Anamika/autonlp-fa-473312409
You can use cURL to access this model: Or Python API:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Anamika/autonlp-fa-473312409 ### Model URL : https://huggingface.co/Anamika/autonlp-fa-473312409 ### Model Description : You can use cURL to access this model: Or Python API:
Anders/itu-ams-summa
https://huggingface.co/Anders/itu-ams-summa
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Andi/bert-tt-ner-1
https://huggingface.co/Andi/bert-tt-ner-1
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Andranik/TestPytorchClassification
https://huggingface.co/Andranik/TestPytorchClassification
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andranik/TestPytorchClassification ### Model URL : https://huggingface.co/Andranik/TestPytorchClassification ### Model Description : No model card New: Create and edit this model card directly on the website!
Andranik/TestQA2
https://huggingface.co/Andranik/TestQA2
This model is a fine-tuned version of ahotrod/electra_large_discriminator_squad2_512 on an unknown dataset. More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andranik/TestQA2 ### Model URL : https://huggingface.co/Andranik/TestQA2 ### Model Description : This model is a fine-tuned version of ahotrod/electra_large_discriminator_squad2_512 on an unknown dataset. More information needed More information needed More information needed The following hyperparameters were used during training:
Andranik/TestQaV1
https://huggingface.co/Andranik/TestQaV1
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AndreLiu1225/t5-news-summarizer
https://huggingface.co/AndreLiu1225/t5-news-summarizer
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AndreLiu1225/t5-news
https://huggingface.co/AndreLiu1225/t5-news
This is a pretrained model that was loaded from t5-base. It has been adapted and changed by changing the max_length and summary_length.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndreLiu1225/t5-news ### Model URL : https://huggingface.co/AndreLiu1225/t5-news ### Model Description : This is a pretrained model that was loaded from t5-base. It has been adapted and changed by changing the max_length and summary_length.
Andres2015/HiggingFaceTest
https://huggingface.co/Andres2015/HiggingFaceTest
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AndrewChar/model-QA-5-epoch-RU
https://huggingface.co/AndrewChar/model-QA-5-epoch-RU
This model is a fine-tuned version of AndrewChar/diplom-prod-epoch-4-datast-sber-QA on sberquad dataset. It achieves the following results on the evaluation set: Модель отвечающая на вопрос по контектсу это дипломная работа Контекст должен содержать не более 512 токенов DataSet SberSQuAD {'exact_match': 54.586, 'f1': 73.644} The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewChar/model-QA-5-epoch-RU ### Model URL : https://huggingface.co/AndrewChar/model-QA-5-epoch-RU ### Model Description : This model is a fine-tuned version of AndrewChar/diplom-prod-epoch-4-datast-sber-QA on sberquad dataset. It achieves the following results on the evaluation set: Модель отвечающая на вопрос по контектсу это дипломная работа Контекст должен содержать не более 512 токенов DataSet SberSQuAD {'exact_match': 54.586, 'f1': 73.644} The following hyperparameters were used during training:
AndrewMcDowell/wav2vec2-xls-r-1B-german
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1B-german
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - DE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-1B-german ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1B-german ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - DE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AndrewMcDowell/wav2vec2-xls-r-1b-arabic
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1b-arabic
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - AR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training: This model's model-index metadata is invalid: Schema validation error. "model-index[0].name" is not allowed to be empty
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-1b-arabic ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1b-arabic ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - AR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training: This model's model-index metadata is invalid: Schema validation error. "model-index[0].name" is not allowed to be empty
AndrewMcDowell/wav2vec2-xls-r-1b-japanese-hiragana-katakana
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1b-japanese-hiragana-katakana
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training: This model's model-index metadata is invalid: Schema validation error. "model-index[0].name" is not allowed to be empty
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-1b-japanese-hiragana-katakana ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-1b-japanese-hiragana-katakana ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training: This model's model-index metadata is invalid: Schema validation error. "model-index[0].name" is not allowed to be empty
AndrewMcDowell/wav2vec2-xls-r-300m-arabic
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-arabic
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-300m-arabic ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-arabic ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AR dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AndrewMcDowell/wav2vec2-xls-r-300m-german-de
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-german-de
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - DE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-300m-german-de ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-german-de ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - DE dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AndrewMcDowell/wav2vec2-xls-r-300m-japanese
https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-japanese
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset. Kanji are converted into Hiragana using the pykakasi library during training and evaluation. The model can output both Hiragana and Katakana characters. Since there is no spacing, WER is not a suitable metric for evaluating performance and CER is more suitable. On mozilla-foundation/common_voice_8_0 it achieved: On speech-recognition-community-v2/dev_data it achieved: It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewMcDowell/wav2vec2-xls-r-300m-japanese ### Model URL : https://huggingface.co/AndrewMcDowell/wav2vec2-xls-r-300m-japanese ### Model Description : This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset. Kanji are converted into Hiragana using the pykakasi library during training and evaluation. The model can output both Hiragana and Katakana characters. Since there is no spacing, WER is not a suitable metric for evaluating performance and CER is more suitable. On mozilla-foundation/common_voice_8_0 it achieved: On speech-recognition-community-v2/dev_data it achieved: It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
AndrewNLP/redditDepressionPropensityClassifiers
https://huggingface.co/AndrewNLP/redditDepressionPropensityClassifiers
No model card New: Create and edit this model card directly on the website!
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : AndrewNLP/redditDepressionPropensityClassifiers ### Model URL : https://huggingface.co/AndrewNLP/redditDepressionPropensityClassifiers ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey1989/bert-multilingual-finetuned-ner
https://huggingface.co/Andrey1989/bert-multilingual-finetuned-ner
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/bert-multilingual-finetuned-ner ### Model URL : https://huggingface.co/Andrey1989/bert-multilingual-finetuned-ner ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey1989/mbart-finetuned-en-to-kk
https://huggingface.co/Andrey1989/mbart-finetuned-en-to-kk
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/mbart-finetuned-en-to-kk ### Model URL : https://huggingface.co/Andrey1989/mbart-finetuned-en-to-kk ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey1989/mbert-finetuned-ner
https://huggingface.co/Andrey1989/mbert-finetuned-ner
This model is a fine-tuned version of bert-base-multilingual-cased on the wikiann dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/mbert-finetuned-ner ### Model URL : https://huggingface.co/Andrey1989/mbert-finetuned-ner ### Model Description : This model is a fine-tuned version of bert-base-multilingual-cased on the wikiann dataset. It achieves the following results on the evaluation set: More information needed More information needed More information needed The following hyperparameters were used during training:
Andrey1989/mbert-finetuned-ner_2
https://huggingface.co/Andrey1989/mbert-finetuned-ner_2
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/mbert-finetuned-ner_2 ### Model URL : https://huggingface.co/Andrey1989/mbert-finetuned-ner_2 ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey1989/mt5-small-finetuned-mlsum-es
https://huggingface.co/Andrey1989/mt5-small-finetuned-mlsum-es
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/mt5-small-finetuned-mlsum-es ### Model URL : https://huggingface.co/Andrey1989/mt5-small-finetuned-mlsum-es ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey1989/mt5-small-finetuned-mlsum-fr
https://huggingface.co/Andrey1989/mt5-small-finetuned-mlsum-fr
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey1989/mt5-small-finetuned-mlsum-fr ### Model URL : https://huggingface.co/Andrey1989/mt5-small-finetuned-mlsum-fr ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey78/my_model_nlp
https://huggingface.co/Andrey78/my_model_nlp
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey78/my_model_nlp ### Model URL : https://huggingface.co/Andrey78/my_model_nlp ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrey78/my_nlp_test_model
https://huggingface.co/Andrey78/my_nlp_test_model
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrey78/my_nlp_test_model ### Model URL : https://huggingface.co/Andrey78/my_nlp_test_model ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrianos/bert-base-greek-punctuation-prediction-finetuned
https://huggingface.co/Andrianos/bert-base-greek-punctuation-prediction-finetuned
This repository is publicly accessible, but you have to accept the conditions to access its files and content. Log in or Sign Up to review the conditions and access this model content. This model is a finetuning of bert-base-greek-uncased as a Token Classifier which predicts at each token which punctuation mark it is followed by. The model preprocesses everything to lowercase and removes all Greek diacritics. For information on pretraining of the Greek Bert model, please refer to Greek Bert Epochs: 5Maximum Sequence Length: 512Learning Rate: 4e−5Batch Size: 16 Finetuning Data:Greek Europarl data available at: https://opus.nlpl.eu/Europarl.php Tokens: 44.1MSentences: 1.6M Punctuation Points Recognised:'.' (0) : Full stop',' (1) : Comma';' (2) : Greek question mark'-' (3) : Dash':' (4) : Semicolon'0' (5) : No punctuation point is following If you are interested in trying out examples and finding the limitations of the model, the starter Python code to use the model is available at Github Repo Using the demo script, we tried out a few brief examples and show the results below The last two examples have identical meanings, the first is written in plain Modern Greek and the latter in the Cypriot Dialect. It is interesting to see the model performs similarly, even if some words and suffixes are out of vocabulary. We would be happy to hear people have finetuned this model with more and diverse datasets, as we expect this to increase robustness. Within our research, improvements to consistency in punctuation prediction have shown to be possible with techniques such as sliding windows (during inference) for larger documents, weighted loss and ensembling of different models. Make sure to cite our work when you further our models with the aforementioned techniques. This model is further work based on the winning submission at Shared Task 2 Sentence End and Punctuation Prediction in NLG Text at SwissText2021.The winning submission is entitled "UZH OnPoint at Swisstext-2021: Sentence End and Punctuation Prediction in NLG Text Through Ensembling of Different Transformers" in the Proceedings of the 6th SwissText Held Online. It is publicly available at http://ceur-ws.org/Vol-2957/sepp_paper2.pdf If you use the model, please cite the following: @inproceedings{ST2021-OnPoint, title={UZH OnPoint at Swisstext-2021: Sentence End and Punctuation Prediction in NLG Text Through Ensembling of Different Transformers}, author={Michail, Andrianos and Wehrli, Silvan and Bucková, Terézia}, booktitle={Proceedings of the 1st Shared Task on Sentence End and Punctuation Prediction in NLG Text (SEPPNLG 2021) at SwissText 2021}, year={2021} } Model Finetuned and released by Andrianos Michail with resources provided by Department of Computational Linguistics, University of Zurich | Github: @Andrian0s | LinkedIn: amichail2
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrianos/bert-base-greek-punctuation-prediction-finetuned ### Model URL : https://huggingface.co/Andrianos/bert-base-greek-punctuation-prediction-finetuned ### Model Description : This repository is publicly accessible, but you have to accept the conditions to access its files and content. Log in or Sign Up to review the conditions and access this model content. This model is a finetuning of bert-base-greek-uncased as a Token Classifier which predicts at each token which punctuation mark it is followed by. The model preprocesses everything to lowercase and removes all Greek diacritics. For information on pretraining of the Greek Bert model, please refer to Greek Bert Epochs: 5Maximum Sequence Length: 512Learning Rate: 4e−5Batch Size: 16 Finetuning Data:Greek Europarl data available at: https://opus.nlpl.eu/Europarl.php Tokens: 44.1MSentences: 1.6M Punctuation Points Recognised:'.' (0) : Full stop',' (1) : Comma';' (2) : Greek question mark'-' (3) : Dash':' (4) : Semicolon'0' (5) : No punctuation point is following If you are interested in trying out examples and finding the limitations of the model, the starter Python code to use the model is available at Github Repo Using the demo script, we tried out a few brief examples and show the results below The last two examples have identical meanings, the first is written in plain Modern Greek and the latter in the Cypriot Dialect. It is interesting to see the model performs similarly, even if some words and suffixes are out of vocabulary. We would be happy to hear people have finetuned this model with more and diverse datasets, as we expect this to increase robustness. Within our research, improvements to consistency in punctuation prediction have shown to be possible with techniques such as sliding windows (during inference) for larger documents, weighted loss and ensembling of different models. Make sure to cite our work when you further our models with the aforementioned techniques. This model is further work based on the winning submission at Shared Task 2 Sentence End and Punctuation Prediction in NLG Text at SwissText2021.The winning submission is entitled "UZH OnPoint at Swisstext-2021: Sentence End and Punctuation Prediction in NLG Text Through Ensembling of Different Transformers" in the Proceedings of the 6th SwissText Held Online. It is publicly available at http://ceur-ws.org/Vol-2957/sepp_paper2.pdf If you use the model, please cite the following: @inproceedings{ST2021-OnPoint, title={UZH OnPoint at Swisstext-2021: Sentence End and Punctuation Prediction in NLG Text Through Ensembling of Different Transformers}, author={Michail, Andrianos and Wehrli, Silvan and Bucková, Terézia}, booktitle={Proceedings of the 1st Shared Task on Sentence End and Punctuation Prediction in NLG Text (SEPPNLG 2021) at SwissText 2021}, year={2021} } Model Finetuned and released by Andrianos Michail with resources provided by Department of Computational Linguistics, University of Zurich | Github: @Andrian0s | LinkedIn: amichail2
Andrija/M-bert-NER
https://huggingface.co/Andrija/M-bert-NER
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/M-bert-NER ### Model URL : https://huggingface.co/Andrija/M-bert-NER ### Model Description : Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Andrija/RobertaFastBPE
https://huggingface.co/Andrija/RobertaFastBPE
from transformers import RobertaTokenizerFast tokenizer = RobertaTokenizerFast.from_pretrained('Andrija/RobertaFastBPE', bos_token="<s>", eos_token="</s>") encoded = tokenizer('Stručnjaci te bolnice, predvođeni dr Alisom Lim') tokenizer.decode(encoded['input_ids'])
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/RobertaFastBPE ### Model URL : https://huggingface.co/Andrija/RobertaFastBPE ### Model Description : from transformers import RobertaTokenizerFast tokenizer = RobertaTokenizerFast.from_pretrained('Andrija/RobertaFastBPE', bos_token="<s>", eos_token="</s>") encoded = tokenizer('Stručnjaci te bolnice, predvođeni dr Alisom Lim') tokenizer.decode(encoded['input_ids'])
Andrija/SRoBERTa-F
https://huggingface.co/Andrija/SRoBERTa-F
Trained on 43GB datasets that contain Croatian and Serbian language for one epochs (9.6 mil. steps, 3 epochs). Leipzig Corpus, OSCAR, srWac, hrWac, cc100-hr and cc100-sr datasets Validation number of exampels run for perplexity:1620487 sentences Perplexity:6.02 Start loss: 8.6 Final loss: 2.0 Thoughts: Model could be trained more, the training did not stagnate.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-F ### Model URL : https://huggingface.co/Andrija/SRoBERTa-F ### Model Description : Trained on 43GB datasets that contain Croatian and Serbian language for one epochs (9.6 mil. steps, 3 epochs). Leipzig Corpus, OSCAR, srWac, hrWac, cc100-hr and cc100-sr datasets Validation number of exampels run for perplexity:1620487 sentences Perplexity:6.02 Start loss: 8.6 Final loss: 2.0 Thoughts: Model could be trained more, the training did not stagnate.
Andrija/SRoBERTa-L-NER
https://huggingface.co/Andrija/SRoBERTa-L-NER
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-L-NER ### Model URL : https://huggingface.co/Andrija/SRoBERTa-L-NER ### Model Description : Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Andrija/SRoBERTa-L
https://huggingface.co/Andrija/SRoBERTa-L
Trained on 6GB datasets that contain Croatian and Serbian language for two epochs (500k steps). Leipzig, OSCAR and srWac datasets
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-L ### Model URL : https://huggingface.co/Andrija/SRoBERTa-L ### Model Description : Trained on 6GB datasets that contain Croatian and Serbian language for two epochs (500k steps). Leipzig, OSCAR and srWac datasets
Andrija/SRoBERTa-NER
https://huggingface.co/Andrija/SRoBERTa-NER
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-NER ### Model URL : https://huggingface.co/Andrija/SRoBERTa-NER ### Model Description : Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Andrija/SRoBERTa-NLP
https://huggingface.co/Andrija/SRoBERTa-NLP
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Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-NLP ### Model URL : https://huggingface.co/Andrija/SRoBERTa-NLP ### Model Description : No model card New: Create and edit this model card directly on the website!
Andrija/SRoBERTa-XL-NER
https://huggingface.co/Andrija/SRoBERTa-XL-NER
Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.
Indicators looking for configurations to recommend AI models for configuring AI agents ### Model Name : Andrija/SRoBERTa-XL-NER ### Model URL : https://huggingface.co/Andrija/SRoBERTa-XL-NER ### Model Description : Named Entity Recognition (Token Classification Head) for Serbian / Croatian languges.