## Dromedary-65B-LoRA HF
These files are the result of merging the [delta weights of IBM's Dromedary 65B LoRA](https://huggingface.co/zhiqings/dromedary-65b-lora-delta-v0) with the original Llama 65B model.
## Repositories available
* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/dromedary-65B-lora-GPTQ)
* [4bit and 5bit GGML models for CPU inference in llama.cpp](https://huggingface.co/TheBloke/dromedary-65B-lora-GGML)
* [float16 unquantised model for GPU](https://huggingface.co/TheBloke/dromedary-65B-lora-HF)
## Discord
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## Thanks, and how to contribute.
Thanks to the [chirper.ai](https://chirper.ai) team!
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If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
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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.