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--- |
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tags: |
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- autotrain |
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- text-classification |
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language: |
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- en |
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widget: |
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- text: " frases-bertimbau-v0.4 This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset." |
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- text: "Model description BERTa is a transformer-based masked language model for the Catalan language. It is based on the [RoBERTA](https://github.com/pytorch/fairseq/tree/master/examples/roberta) base model and has been trained on a medium-size corpus collected from publicly available corpora and crawlers" |
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- text: "Model description More information needed" |
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datasets: |
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- davanstrien/autotrain-data-dataset-mentions |
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co2_eq_emissions: |
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emissions: 0.008999666562870793 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Binary Classification |
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- Model ID: 3390592983 |
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- CO2 Emissions (in grams): 0.0090 |
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## Validation Metrics |
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- Loss: 0.014 |
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- Accuracy: 0.997 |
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- Precision: 0.998 |
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- Recall: 0.997 |
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- AUC: 1.000 |
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- F1: 0.998 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/davanstrien/autotrain-dataset-mentions-3390592983 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("davanstrien/autotrain-dataset-mentions-3390592983", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-dataset-mentions-3390592983", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
