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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.