--- datasets: - stingning/ultrachat --- This is [openbmb/UltraLM-13b](https://huggingface.co/openbmb/UltraLM-13b) recovered with [huggyllama/llama-13b](https://huggingface.co/huggyllama/llama-13b) and quantized to 4bit GPTQ with the following config: ```python quantize_config = BaseQuantizeConfig( bits=4, group_size=32, desc_act=True, ) ``` # Original Model Card: # UltraLM-13b This is UltraLM-13b delta weights, a chat language model trained upon [UltraChat](https://github.com/thunlp/UltraChat) ## Model Details ### Model Description The model is fine-tuned based on LLaMA-13b with a multi-turn chat-format template as below ``` User: instruction 1 Assistant: response 1 User: instruction 2 Assistant: response 2 ... ``` - **License:** UltraLM is based on LLaMA and should be used under LLaMA's [model license](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md). - **Finetuned from model:** LLaMA-13b - **Finetuned on data:** [UltraChat](https://github.com/thunlp/UltraChat) ### Model Sources - **Repository:** [UltraChat](https://github.com/thunlp/UltraChat) - **Paper:** [arxiv](https://arxiv.org/abs/2305.14233) - **Demo:** [More Information Needed] ## Uses To use this model, you need to [recover](https://github.com/thunlp/UltraChat/tree/main/UltraLM) the full model from the delta weights and perform inference following the template below: ``` [Optional]User: system prompt User: user input Assistant: ```