Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
Paper
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2305.14233
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Published
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6
This is openbmb/UltraLM-13b recovered with huggyllama/llama-13b and quantized to 4bit GPTQ with the following config:
quantize_config = BaseQuantizeConfig(
bits=4,
group_size=32,
desc_act=True,
)
This is UltraLM-13b delta weights, a chat language model trained upon UltraChat
The model is fine-tuned based on LLaMA-13b with a multi-turn chat-format template as below
User: instruction 1<eos_token>
Assistant: response 1<eos_token>
User: instruction 2<eos_token>
Assistant: response 2<eos_token>
...
To use this model, you need to recover the full model from the delta weights and perform inference following the template below:
[Optional]User: system prompt<eos_token>
User: user input<eos_token>
Assistant: