Dromedary-65B-LoRA HF
These files are the result of merging the delta weights of IBM's Dromedary 65B LoRA with the original Llama 65B model.
Repositories available
- 4bit GPTQ models for GPU inference
- 4bit and 5bit GGML models for CPU inference in llama.cpp
- float16 unquantised model for GPU
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Original Dromedary Model Card
See https://github.com/IBM/Dromedary#model-weights for instructions.
Model details
Model type: Dromedary is an open-source self-aligned language model trained with minimal human supervision. The base language model is LLaMA-65b, based on the transformer architecture.
Model date: Dromedary was trained between April 2023 and May 2023, but its knowledge only goes up until Sept-2021.
Organizations developing the model: The Dromedary team as a joint effort between CMU and IBM.
Paper or resources for more information: https://mitibmdemos.draco.res.ibm.com/dromedary
License: LLaMA's Non-commercial bespoke license
Where to send questions or comments about the model: https://github.com/IBM/Dromedary/issues
Intended use
Primary intended uses: The primary use of Dromedary is research on the alignment of large language models.
Primary intended users: The primary intended users of the model are researchers in artificial intelligence.
Delta weights
We use the following configuration for the LoRA weights:
--lora_target_modules='[q_proj,k_proj,v_proj,o_proj]' \
--lora_r=16 \
Training dataset
Fewer than 300 lines of human annotations (including < 200 seed prompts, 16 generic principles, and 5 exemplars for in-context learning),
Evaluation dataset
We evaluate Dromedary on TruthfulQA and HHH Eval, as well as Vicuna benchmark questions.
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