license: creativeml-openrail-m
language:
- en
thumbnail: null
tags:
- text generation
- conversational
inference: false
Pygmalion 6B
Model description
Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's GPT-J-6B.
Warning: This model is NOT suitable for use by minors. It will output X-rated content under certain circumstances.
Training data
The fine-tuning dataset consisted of 56MB of dialogue data gathered from multiple sources, which includes both real and partially machine-generated conversations.
Training procedure
Model weights were initialized from the uft-6b ConvoGPT model made available in this commit.
The model was then further fine-tuned on ~48.5 million tokens for ~5k steps on 4 NVIDIA A40s using DeepSpeed.
Intended use
The easy way
We provide a notebook with a Gradio UI for playing around with the model without having to manually format inputs. This notebook can be found here.
The manual way
The model can be used as a regular text generation model, but it'll perform best if the input prompt adheres to the following format:
[CHARACTER]'s Persona: [A few sentences about the character you want the model to play]
<START>
[DIALOGUE HISTORY]
You: [Your input message here]
[CHARACTER]:
Where [CHARACTER] is, as you can probably guess, the name of the character you want the model to portray, <START> should be used verbatim as a delimiter token to separate persona and scenario data from the dialogue, and [DIALOGUE HISTORY] is chat history so the model can have some conversational context to draw from. Ideally it'll be pairs of messages like:
[CHARACTER]: [some dialogue here]
You: [your response to the dialogue above]
Apart from chat history, you can also just add example conversations in [DIALOGUE HISTORY] to show how the character should speak - ideally at the beginning, so it doesn't get confused as to what's conversation history vs. character definition.
Known issues
We haven't played around with the model enough to enumerate them. Feel free to give us some feedback!
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 36.37 |
| ARC (25-shot) | 40.53 |
| HellaSwag (10-shot) | 67.47 |
| MMLU (5-shot) | 25.73 |
| TruthfulQA (0-shot) | 32.53 |
| Winogrande (5-shot) | 62.51 |
| GSM8K (5-shot) | 2.05 |
| DROP (3-shot) | 23.75 |