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README.md

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+## Dromedary-65B-LoRA GGML
+
+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.
+
+This repo contains GGML files for for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp).
+
+## 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)
+
+## Provided files
+| Name | Quant method | Bits | Size | RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+`dromedary-lora-65B.ggml.q4_0.bin` | q4_0 | 4bit | 40.8GB | 43GB | Maximum compatibility |
+`dromedary-lora-65B.ggml.q4_2.bin` | q4_2 | 4bit | 40.8GB | 43GB | Best compromise between resources, speed and quality |
+`dromedary-lora-65B.ggml.q5_0.bin` | q5_0 | 5bit | 44.9GB | 47GB | Brand new 5bit method. Potentially higher quality than 4bit, at cost of slightly higher resources. |
+`dromedary-lora-65B.ggml.q5_1.bin` | q5_1 | 5bit | 49GB | 51GB | Brand new 5bit method. Slightly higher resource usage than q5_0.|
+
+* The q4_0 file provides lower quality, but maximal compatibility. It will work with past and future versions of llama.cpp
+* The q4_2 file offers the best combination of performance and quality. This format is still subject to change and there may be compatibility issues, see below.
+* The q5_0 file is using brand new 5bit method released 26th April. This is the 5bit equivalent of q4_0.
+* The q5_1 file is using brand new 5bit method released 26
+
+# Original Dromedary Model Card
+ 
+See https://github.com/IBM/Dromedary#model-weights for instructions.
+
+## Model details
+
+<div align="center">
+
+<img src="https://raw.githubusercontent.com/IBM/Dromedary/main/assets/images/dromedary_logo.svg" alt="Dromedary Logo"/>
+
+</div>
+
+**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.