piotr25691
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Name override with rsLoRA(rank=128, alpha=256)
Browse files- README.md +4 -3
- model-00001-of-00002.safetensors +1 -1
- model-00002-of-00002.safetensors +1 -1
- tokenizer.json +2 -2
README.md
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base_model: meta-llama/Llama-3.2-3B-Instruct
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datasets:
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- KingNish/reasoning-base-20k
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language:
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- en
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license: llama3.2
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# Model Description
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A
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Here is what inference code you should use:
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```py
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from transformers import AutoModelForCausalLM, AutoTokenizer
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reasoning_ids = model.generate(**reasoning_inputs, max_new_tokens=MAX_REASONING_TOKENS)
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reasoning_output = tokenizer.decode(reasoning_ids[0, reasoning_inputs.input_ids.shape[1]:], skip_special_tokens=True)
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# Generate answer
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messages.append({"role": "reasoning", "content": reasoning_output})
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base_model: meta-llama/Llama-3.2-3B-Instruct
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datasets:
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- KingNish/reasoning-base-20k
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- piotr25691/thea-name-overrides
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language:
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- en
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license: llama3.2
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# Model Description
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A reasoning Llama 3.2 3B model trained on reasoning data.
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It has been trained using improved training code, and gives an improved performance.
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Here is what inference code you should use:
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```py
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from transformers import AutoModelForCausalLM, AutoTokenizer
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reasoning_ids = model.generate(**reasoning_inputs, max_new_tokens=MAX_REASONING_TOKENS)
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reasoning_output = tokenizer.decode(reasoning_ids[0, reasoning_inputs.input_ids.shape[1]:], skip_special_tokens=True)
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print("REASONING: " + reasoning_output)
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# Generate answer
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messages.append({"role": "reasoning", "content": reasoning_output})
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model-00001-of-00002.safetensors
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model-00002-of-00002.safetensors
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tokenizer.json
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