Qwen3-8B-Instruct-2512-SFT/README.md

library_name, license, license_link, pipeline_tag, base_model

library_name	license	license_link	pipeline_tag	base_model
transformers	apache-2.0	https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE	text-generation	Qwen/Qwen3-8B

Qwen3-8B-Instruct-2512-SFT

NOTE：This model is the Instruct-aligned variant, and it will not generate <think></think> blocks in its outputs. Additionally, there is no need to specify enable_thinking=False anymore.

Among them, the 8B and 14B SFT and DFT variants are obtained via full-parameter fine-tuning, while the 32B models are trained using LoRA due to hardware resource constraints.
The dataset used is the Chinese Distillation Dataset based on Qwen3-235B-2507.available at:Chinese-Qwen3-235B-2507-Distill-data-110k
For details and code regarding model training and quantization, please seeTraining and Quantization Guide
Here is the list of models released in this version:

Model	4-bit AWQ		8-bit FP8	GPTQ		NVIDIA FP4		Weight-Activation
	AWQ	AWQ-asym		INT4	INT8	NVFP4	NVFP4-A16	W4A16	W8A8
Qwen3-8B-Instruct-2512-DFT	AWQ	awq-asym	FP8	GPTQ(int4)	GPTQ(int8)	NVFP4	NVFP4A16	W4A16	W8A8
Qwen3-8B-Instruct-2512-SFT	AWQ	awq-asym	FP8	GPTQ(int4)	GPTQ(int8)	NVFP4	NVFP4A16	W4A16	W8A8
Qwen3-14B-Instruct-2512-DFT	AWQ	awq-asym	FP8	GPTQ(int4)	GPTQ(int8)	NVFP4	NVFP4A16	W4A16	W8A8
Qwen3-14B-Instruct-2512-SFT	AWQ	awq-asym	FP8	GPTQ(int4)	GPTQ(int8)	NVFP4	NVFP4A16	W4A16	W8A8
Qwen3-32B-Instruct-2512-DFT	AWQ	awq-asym	FP8	GPTQ(int4)	GPTQ(int8)	NVFP4	NVFP4A16	W4A16	W8A8

【Dependencies】

vllm>=0.10.2
transformers>=4.56.1