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Model: breitburg/pure-reasoning-7b-230726
Source: Original Platform

README.md

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+---
+base_model: breitburg/pure-7b-210726
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- reasoning
+- chain-of-thought
+license: apache-2.0
+language:
+- en
+---
+
+# pure-reasoning-7b-230726
+
+A reasoning ("thinking") fine-tune of [breitburg/pure-7b-210726](https://huggingface.co/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|>`.
+
+- **Developed by:** breitburg
+- **License:** apache-2.0
+- **Finetuned from:** breitburg/pure-7b-210726
+- **Dataset:** [breitburg/reasonable-chats](https://huggingface.co/datasets/breitburg/reasonable-chats)
+- **Date:** 23 July 2026
+- **Method:** LoRA SFT (Unsloth + TRL). Two new vocab tokens `<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.
+
+## Usage
+
+```python
+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](https://github.com/unslothai/unsloth).