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INCModel2/Qwen3.8-27B-W4A16-RTN-CT-AutoRound
Qwen3.8-27B-W4A16-RTN-CT-AutoRound is a machine learning model from INCModel2. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model is an int4 model with groupsize 128 of Qwen3.8-27B generated by intel/auto-round with RTN mode. Please follow the license of the original model.
Downloads · 30 days
147
37% of all-time downloads
All-time downloads
393
Public
Parameters
6.3B
19.5 GB on disk
Likes
1
Public
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.safetensors19.5 GB · 100%
How the weights are stored.
I3224.3B · 88%
From the Hugging Face model README
This model is an int4 model with group_size 128 of Qwen3.8-27B generated by intel/auto-round with RTN mode. Please follow the license of the original model.
auto-round Qwen/Qwen3.8-27B \
--model_free \
--scheme W4A16 \
--ignore_layers "visual,lm_head,embed_tokens,mtp" \
--format llm_compressor \
--device auto \
--output_dir "./qwen3.8-27B-W4A16-CT-AutoRound"
The model can produce factually incorrect output, and should not be relied on to produce factually accurate information. Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
Therefore, before deploying any applications of the model, developers should perform safety testing.
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
Here are a couple of useful links to learn more about Intel's AI software:
The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model. Please consult an attorney before using this model for commercial purposes.
@article{cheng2023optimize, title={Optimize weight rounding via signed gradient descent for the quantization of llms}, author={Cheng, Wenhua and Zhang, Weiwei and Shen, Haihao and Cai, Yiyang and He, Xin and Lv, Kaokao and Liu, Yi}, journal={arXiv preprint arXiv:2309.05516}, year={2023} }