Teja-Gollapudi
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Update README.md
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README.md
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---
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license: cc-by-sa-3.0
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datasets:
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- VMware/open-instruct
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language:
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- en
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library_name: transformers
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## License
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- <b>Commercially Viable </b>
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-
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- Mosaic/Dolly-HHRLHF + filtered OASST1 - cc by 3.0
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Subset of COT SUBMIX (FROM FLAN V2) Zeroshot examples
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- gsmk8 - MIT
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- aqua - MIT
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- qasc - Apache 2.0
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- Language Model, ([openlm-research/open_llama_v2_7b](https://huggingface.co/openlm-research/open_llama_v2_7b)) is under apache-2.0
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## Nomenclature
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- Model : Open-llama-v2
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- Model Size: 7B parameters
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- Dataset: Open-instruct
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## Use in Transformers
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = 'VMware/open-llama-7b-open-instruct'
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
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---
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license: cc-by-sa-3.0
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datasets:
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- VMware/open-instruct
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language:
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- en
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library_name: transformers
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## License
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- <b>Commercially Viable </b>
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<b>Open-instruct <br>
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Open-instruct-v1
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- Mosaic/Dolly-HHRLHF + filtered OASST1 - cc by 3.0
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Subset of COT SUBMIX (FROM FLAN V2) Zeroshot examples
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- gsmk8 - MIT
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- aqua - MIT
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- qasc - Apache 2.0
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<br>
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- Language Model, ([openlm-research/open_llama_v2_7b](https://huggingface.co/openlm-research/open_llama_v2_7b)) is under apache-2.0
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- Dataset ([VMware/open-instruct](https://huggingface.co/datasets/VMware/open-instruct)) is under cc-by-sa-3.0
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## Nomenclature
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- Model : Open-llama-v2
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- Model Size: 7B parameters
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- Dataset: Open-instruct
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## Use in Transformers
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = 'VMware/open-llama-7b-v2-open-instruct'
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
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