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breitburg/pure-reasoning-7b-230726
pure-reasoning-7b-230726 is a text generation model from breitburg. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
A reasoning ("thinking") fine-tune of breitburg/pure-7b-210726. Given a chat prompt it first produces a <think...</think reasoning block, then commits to an answer, and stops on <|imend|.
Downloads · 30 days
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From the Hugging Face model README
A reasoning ("thinking") fine-tune of breitburg/pure-7b-210726.
Given a chat prompt it first produces a <think>...</think> reasoning block, then commits to an
answer, and stops on <|im_end|>.
<think>/</think> were added and
trained full-rank on embed_tokens/lm_head; the chat template folds the dataset's per-turn
reasoning traces into <think> blocks.from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("breitburg/pure-reasoning-7b-230726")
model = AutoModelForCausalLM.from_pretrained("breitburg/pure-reasoning-7b-230726", device_map="cuda")
msgs = [{"role": "user", "content": "What causes the seasons on Earth?"}]
inputs = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt").to("cuda")
out = model.generate(inputs, max_new_tokens=300)
print(tok.decode(out[0][inputs.shape[1]:], skip_special_tokens=False))
Trained 2x faster with Unsloth.