---
license: apache-2.0
inference: false
---

# Dromedary Model Card

**NOTE: This "delta model" cannot be used directly.**  
Users have to apply it on top of the original LLaMA weights to get actual Dromedary weights.  
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.