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--- |
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language: |
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- en |
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--- |
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### Description: |
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This is a multipurpose chat / chat instruct hybrid model in the same vein as the Pygmalion team's Metharme. It uses a curated pile of training data that has been normalized into a consistent training format. It has been trained on a wide array of one shot instructions, multi round instructions, and role playing scenarios. |
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### Prompt format: |
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Metharme |
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The prompt should start with the cursor on the same line directly after "<|model|>" with no space. The following are all valid formats and can be extended to as many rounds as desired. |
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``` |
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<|system|>system message here<|user|>user message here<|model|> |
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``` |
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``` |
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<|system|>system message here<|user|>user message here<|model|>model message<|user|>user message here<|model|> |
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``` |
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``` |
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<|system|>system message here<|model|> |
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``` |
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``` |
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<|system|>system message here<|model|>model message<|user|>user message here<|model|> |
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``` |
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Some example prompts: |
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``` |
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<|system|>The following is a transcript between a helpful assistant and a user.<|user|>Why is the sky blue?<|model|> |
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``` |
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``` |
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<|system|>You are a Virtual Story Generator. You take the user's input and create an excellent and captivating story that goes in that direction. Use an abundance of sensory descriptions and eloquent prose.<|user|>Alpha Centauri has fallen, to the bears. This is a point of view tale about a soldier on the ground.<|model|> |
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``` |
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``` |
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<|system|>You are a professional editor with decades of experience, help the user with any task they have for you.<|user|>Can you rewrite this to flow better? "I knew I probably shouldnt have done that but oh well"<|model|> |
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``` |
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More will be added at a later date. |
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### Perplexity Benchmarks: |
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- TBA |
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### Training information: |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="150" height="24"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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- GPTQ 4 bit LoRA |
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- 7 Epochs |
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- 64 / 32 R / A |
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- 2048 Cutoff |
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- 18 hours on 4x RTX 4090s |
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### Data used in training: |
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- TBA |
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### Models used: |
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For training: |
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https://huggingface.co/PocketDoc/llama-13b-gptq-4bit-128g |
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For merging: |
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https://huggingface.co/PocketDoc/Dans-PersonalityEngine-13b-LoRA |
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and |
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https://huggingface.co/huggyllama/llama-13b |
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### Disclaimer: |
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It has not been aligned and no warranty is given for the quality or safety of its outputs. |
