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Equall
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Model Details
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Equall
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
You can use it for legal use cases that involves generation.
Here's how you can run the model using the pipeline() function from 🤗 Transformers:
python
# Install transformers from source - only needed for versions <= v4.34# pip install git+https://github.com/huggingface/transformers.git# pip install accelerateimport torchfrom transformers import pipelinepipe = pipeline("text-generation", model="Equall/Saul-Instruct-v1", torch_dtype=torch.bfloat16, device_map="auto")# We use the tokenizer’s chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templatingmessages = [{"role": "user", "content": "[YOUR QUERY GOES HERE]"},]prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)outputs = pipe(prompt, max_new_tokens=256, do_sample=False)print(outputs[0]["generated_text"])
This model is built upon the technology of LLM, which comes with inherent limitations. It may occasionally generate inaccurate or nonsensical outputs. Furthermore, being a 7B model, it's anticipated to exhibit less robust performance compared to larger models, such as the 70B variant.
BibTeX:
bibtex
@misc{colombo2024saullm7b,title={SaulLM-7B: A pioneering Large Language Model for Law},author={Pierre Colombo and Telmo Pessoa Pires and Malik Boudiaf and Dominic Culver and Rui Melo and Caio Corro and Andre F. T. Martins and Fabrizio Esposito and Vera Lúcia Raposo and Sofia Morgado and Michael Desa},year={2024},eprint={2403.03883},archivePrefix={arXiv},primaryClass={cs.CL}}