---
datasets:
- c-s-ale/alpaca-gpt4-data
- Open-Orca/OpenOrca
- Intel/orca_dpo_pairs
- allenai/ultrafeedback_binarized_cleaned
- HuggingFaceH4/no_robots
license: cc-by-nc-4.0
language:
  - en
library_name: ExLlamaV2
pipeline_tag: text-generation
tags:
  - Mistral
  - SOLAR
  - Quantized Model
  - exl2
base_model:
  - rishiraj/meow
---

# exl2 quants for meow

This repository includes the quantized models for the [meow](https://huggingface.co/rishiraj/meow) model by [Rishiraj Acharya](https://huggingface.co/rishiraj). meow is a fine-tune of [SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0) with the [no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) dataset.

## Current models

| exl2 BPW | Model Branch | Model Size | Minimum VRAM (4096 Context) |
|-|-|-|-|
| 2-Bit | main | 3.28 GB | 6GB GPU |
| 4-Bit | 4bit | 5.61 GB | 8GB GPU |
| 5-Bit | 5bit | 6.92 GB | 10GB GPU, 8GB with swap |
| 6-Bit | 6bit | 8.23 GB | 10GB GPU |
| 8-Bit | 8bit | 10.84 GB | 12GB GPU |

### Note

Using a 12GB Nvidia GeForce RTX 3060 I got on average around 20 tokens per second on the 8-bit quant in full 4096 context.

## Where to use

There are a couple places you can use an exl2 model, here are a few:

- [oobabooga's Text Gen Webui](https://github.com/oobabooga/text-generation-webui)
  - When using the downloader, make sure to format like this: Anthonyg5005/rishiraj-meow-10.7B-exl2**\:QuantBranch**
- [tabbyAPI](https://github.com/theroyallab/tabbyAPI)
- [ExUI](https://github.com/turboderp/exui)
- [KoboldAI](https://github.com/henk717/KoboldAI) (Clone repo, don't use snapshot)

# WARNING
Model cannot be used commercially due to the Alpaca dataset license. Only use this model for research purposes or personal use.