---
datasets:
  - PygmalionAI/PIPPA
  - lemonilia/LimaRP
---

## GPTQ

2048 sequence length

VMware/open-instruct dataset

## Training

[axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
on a 8x nvidia a40 gpu cluster.

the a40 GPU cluster has been graciously provided by [Arc Compute](https://www.arccompute.io/).

rank 16 qlora (all modules) tune

base model mistralai/Mistral-7B-v0.1 tuned on koishi commit 6e675d1 for one epoch

then tuned on pippa 6412b0c for one epoch (metharme completion)

then tuned on limarp Version 2023-10-19 for 2 epochs in metharme completion format

## Prompting

The current model version has been trained on prompts using three different roles, which are denoted by the following tokens: `<|system|>`, `<|user|>` and `<|model|>`.

The `<|system|>` prompt can be used to inject out-of-channel information behind the scenes, while the `<|user|>` prompt should be used to indicate user input. The `<|model|>` token should then be used to indicate that the model should generate a response. These tokens can happen multiple times and be chained up to form a conversation history.