Improve model card: Add pipeline tag, library_name, and sample usage

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by nielsr HF Staff - opened
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  1. README.md +66 -2
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  ---
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- license: llama3.1
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  base_model:
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  - meta-llama/Llama-3.1-8B-Instruct
 
 
 
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  ---
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  # RACE-CoT-Extractor-Llama-8B
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  This is the CoT-Extractor used in the paper "[Joint Evaluation of Answer and Reasoning Consistency for Hallucination Detection in Large Reasoning Models](https://arxiv.org/abs/2506.04832)," which extracts the long reasoning process of a reasoning model into a CoT that only includes essential steps.
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- For details on the prompt format, please refer to our [GitHub repository](https://github.com/bebr2/RACE).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
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  base_model:
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  - meta-llama/Llama-3.1-8B-Instruct
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+ license: llama3.1
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+ pipeline_tag: text-generation
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+ library_name: transformers
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  ---
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  # RACE-CoT-Extractor-Llama-8B
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  This is the CoT-Extractor used in the paper "[Joint Evaluation of Answer and Reasoning Consistency for Hallucination Detection in Large Reasoning Models](https://arxiv.org/abs/2506.04832)," which extracts the long reasoning process of a reasoning model into a CoT that only includes essential steps.
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+ For details on the prompt format, please refer to our [GitHub repository](https://github.com/bebr2/RACE).
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+
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+ ## Sample Usage
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+
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+ This model can be used directly with the Hugging Face `transformers` library to extract concise reasoning steps from a longer thought process.
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+
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "bebr2/RACE-CoT-Extractor-Llama-8B"
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+ tokenizer = AutoTokenizer.from_pretrained(model_id)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto"
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+ )
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+
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+ long_reasoning = """Okay, so I need to figure out if Scott Derrickson and Ed Wood were the same nationality. I'm not entirely sure who each of them is, so I'll start by recalling what I know about them.
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+
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+ First, I think Ed Wood is an actor. I remember hearing his name in the context of some movies. Maybe "The Lord of the Rings" or something similar? I think he's from the UK because I've heard him speak in British accents and I believe he's associated with British productions.
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+
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+ Now, Scott Derrickson. I'm not as familiar with him. I think he might be an actor too, but I'm not sure about his nationality. I'll try to remember any movies or shows he's been in. Maybe "The Social Network"? Wait, isn't that directed by David Fincher? Or was that someone else? Hmm, I'm a bit confused there. Maybe I should look up some of his work. I think he's been in "The Devil's Advocate" and "The Intern" as well. I'm not sure about his nationality, though.
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+
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+ Wait, I think I heard somewhere that Scott Derrickson is of mixed ethnicity. Maybe he's half-African American and half-Caribbean? That could mean he's British by blood but has some African heritage. If that's the case, then he might be British, similar to Ed Wood.
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+
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+ But I'm not entirely certain. I should double-check. Ed Wood is definitely British, as he's been in many British films and has a strong British accent. For Scott Derrickson, I think he's of mixed descent, possibly with some British influence, but I'm not sure if he's considered British by nationality. Nationality can be tricky because of mixed heritage, but often in such cases, the person's place of birth is considered. If he was born in the UK, even with mixed ethnicity, he'd be British.
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+
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+ So, putting it together, both are likely British, even if their nationalities are a bit more complex due to mixed heritage. Therefore, they might share the same nationality, which is British.
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+ """
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+
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+ prompt_text = f"Extract the essential reasoning steps from the following thought process:
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+
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+ {long_reasoning}"
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+
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+ messages = [
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+ {"role": "user", "content": prompt_text}
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+ ]
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+
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+ input_ids = tokenizer.apply_chat_template(
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+ messages,
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+ add_generation_prompt=True,
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+ return_tensors="pt"
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+ ).to(model.device)
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+
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+ outputs = model.generate(
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+ input_ids,
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+ max_new_tokens=256,
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+ do_sample=False,
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+ temperature=0.01,
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+ top_p=0.9,
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+ eos_token_id=tokenizer.eos_token_id
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+ )
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+
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+ generated_text = tokenizer.decode(outputs[0][input_ids.shape[1]:], skip_special_tokens=True)
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+ print(generated_text)
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+ # Expected output (may vary slightly due to model stochasticity but should be a concise list of reasoning steps):
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+ # Ed Wood is a British actor known for British productions.
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+ # Scott Derrickson's nationality is uncertain, possibly of mixed descent with British influence.
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+ # Ed Wood is definitely British.
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+ # Both are likely British, despite complex heritage, if born in the UK.
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+ # Therefore, they might share British nationality.
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+ ```