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Model: glogwa68/Qwen3-0.6B-DISTILL-glm-4.7-think
Source: Original Platform

README.md

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+---
+base_model: Qwen/Qwen3-0.6B
+library_name: transformers
+license: apache-2.0
+language:
+- en
+- fr
+tags:
+- granite
+- fine-tuned
+- conversational
+- distillation
+- thinking
+- reasoning
+datasets:
+- TeichAI/glm-4.7-2000x
+pipeline_tag: text-generation
+---
+
+# Qwen3-0.6B-DISTILL-glm-4.7-think
+
+This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) trained on high-reasoning conversational data from GLM 4.7 by Z.ai.
+
+## Model Details
+
+- **Base Model:** Qwen/Qwen3-0.6B
+- **Fine-tuning Dataset:** TeichAI/glm-4.7-2000x
+- **Context Length:** 1048576 tokens
+- **Special Feature:** Thinking/Reasoning with `<think>` tags
+
+## Usage
+
+### Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("glogwa68/Qwen3-0.6B-DISTILL-glm-4.7-think")
+tokenizer = AutoTokenizer.from_pretrained("glogwa68/Qwen3-0.6B-DISTILL-glm-4.7-think")
+
+messages = [{"role": "user", "content": "Hello, how are you?"}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
+outputs = model.generate(inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Training Details
+
+- **Epochs:** 2
+- **Learning Rate:** 2e-5
+- **Batch Size:** 8 (with gradient accumulation)
+- **Precision:** FP16
+- **Hardware:** Multi-GPU with DeepSpeed ZeRO-3
+
+## License
+
+Apache 2.0