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Model: modrill/qwen3-4b-think-baseline-full-sft
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-4B-Base
+tags:
+  - qwen3
+  - code
+  - sft
+  - full-sft
+  - think
+  - llama-factory
+language:
+  - en
+  - zh
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Qwen3-4B Code SFT - Think Baseline (Full SFT)
+
+Full-parameter supervised fine-tuning (not LoRA) of [Qwen/Qwen3-4B-Base](https://huggingface.co/Qwen/Qwen3-4B-Base) on the think_all dataset with thinking mode enabled.
+
+**This repo contains native full fine-tuned weights** (single `model.safetensors`, ~7.5 GB). For LoRA adapters merged into base weights, see [modrill/qwen3-4b-think-baseline-lora-sft](https://huggingface.co/modrill/qwen3-4b-think-baseline-lora-sft).
+
+## Model Details
+
+- **Base model:** Qwen/Qwen3-4B-Base
+- **Fine-tuning:** Full SFT (DeepSpeed ZeRO-3), finetuning_type: full
+- **Dataset:** think_all
+- **Mode:** Think (`enable_thinking=true`)
+- **Training cutoff length:** 24576 tokens
+- **Epochs:** 2
+- **Learning rate:** 2e-5
+- **Train loss:** ~0.67
+- **Finished:** 2026-06-08
+
+## Usage
+
+### HuggingFace Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "modrill/qwen3-4b-think-baseline-full-sft"
+tok = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, trust_remote_code=True, torch_dtype="auto", device_map="auto"
+)
+```
+
+### vLLM
+
+```bash
+python -m vllm.entrypoints.openai.api_server \
+  --model modrill/qwen3-4b-think-baseline-full-sft \
+  --served-model-name think-baseline-full \
+  --port 8801
+```
+
+## Inference Tips
+
+- Set `enable_thinking=true` in the chat template
+- Recommended `max_tokens`: 24576
+
+## License
+
+Apache 2.0, consistent with the Qwen3 base model license.