transformers mistral text-generation dataset:ewof/koishi-instruct-metharme autotrain_compatible endpoints_compatible text-generation-inference 4-bit gptq region:us
---
datasets:
  - ewof/koishi-instruct-metharme
---

## GPTQ

4096 sequence length

VMware/open-instruct dataset

## Training

[axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
on a 6x nvidia a40 gpu cluster.

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

trained on koishi commit 6e675d1 for one epoch

## Base Model

rank 16 lora tune of mistralai/Mistral-7B-v0.1 (all modules, merged)

## 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.