[Request] Great work! Do you have plans to also create GLM-5.1-AWQ?
GLM-5.1 has been released https://huggingface.co/zai-org/GLM-5.1. Are you planning on also creating a AWQ version of this?
downloading it 🥹
Hey, sorry for the naive question but what caliberation data did you use - the default data is from pileeval as shown in the AutoAWQ library. Given that this model has a chat template did you any chat data (e.g. smoltalk) or did you just use the default AutoAWQ settings. This info would be immensely helpful.
Default caliberation data used in AutoAWQ: https://github.com/casper-hansen/AutoAWQ/blob/88e4c76b20755db275574e6a03c83c84ba3bece5/awq/models/base.py#L150
Hey, sorry for the naive question but what caliberation data did you use - the default data is from pileeval as shown in the AutoAWQ library. Given that this model has a chat template did you any chat data (e.g. smoltalk) or did you just use the default AutoAWQ settings. This info would be immensely helpful.
Default caliberation data used in AutoAWQ: https://github.com/casper-hansen/AutoAWQ/blob/88e4c76b20755db275574e6a03c83c84ba3bece5/awq/models/base.py#L150
Reference readme, using data-free quantization (no calibration dataset required).
Thanks for the clarification 👍
I was hoping to find a QuantTrio GLM-5.1-AWQ quantization as we were quite happy with your GLM-5-AWQ variant.
Today I realized that someone else was quicker: https://huggingface.co/cyankiwi/GLM-5.1-AWQ-4bit
Would be nice to know if you plan with similar settings or a different configuration.
This is also why I've been waiting for you guys to release 5.1 version as I am happy with your glm-5 version. Yesterday, I started to put together some code to do it myself based on llm-compressor as I didnt hear back from you guys but later thought maybe its better to wait as you have more experience.