text-generation en dataset:ehartford/dolphin dataset:jondurbin/airoboros-2.2.1 dataset:ehartford/dolphin-coder dataset:teknium/openhermes dataset:ise-uiuc/Magicoder-OSS-Instruct-75K dataset:ise-uiuc/Magicoder-Evol-Instruct-110K dataset:LDJnr/Capybara license:apache-2.0 region:us
---
datasets:
- ehartford/dolphin
- jondurbin/airoboros-2.2.1
- ehartford/dolphin-coder
- teknium/openhermes
- ise-uiuc/Magicoder-OSS-Instruct-75K
- ise-uiuc/Magicoder-Evol-Instruct-110K
- LDJnr/Capybara
language:
- en
license: apache-2.0
quantized_by: bartowski
pipeline_tag: text-generation
---

## Exllama v2 Quantizations of UNA-dolphin-2.6-mistral-7b-dpo-laser

Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.

# The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)

Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.

Original model: https://huggingface.co/fblgit/UNA-dolphin-2.6-mistral-7b-dpo-laser

Model Size: 7b

| Branch | Bits | lm_head bits | Dataset | Size | Description |
| ----- | ---- | ------- | ------- | ------ | ------------ |
| [8_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/8_0) | 8.0 | 8.0 | Default | 9.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/6_5) | 6.5 | 8.0 | Default | 8.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
| [5_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/5_0) | 5.0 | 6.0 | Default | 7.4 GB | Slightly lower perplexity vs 6.5. |
| [4_0](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/4_0) | 4.0 | 6.0 | Default | 6.5 GB | Just under GPTQ equivalent bits per weight. |
| [3_5](https://huggingface.co/Bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2/tree/3_5) | 3.5 | 6.0 | Default | 6.1 GB | Lower quality, only use if you have to. |

All VRAM requirements estimated from 16k context. For 32k context add ~2 GB.

## Download instructions

With git:

```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2
```

With huggingface hub (credit to TheBloke for instructions):

```shell
pip3 install huggingface-hub
```

To download the `main` (only useful if you only care about measurement.json) branch to a folder called `UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2`:

```shell
mkdir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2
huggingface-cli download bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --local-dir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --local-dir-use-symlinks False
```

To download from a different branch, add the `--revision` parameter:

```shell
mkdir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2-6_5
huggingface-cli download bartowski/UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2 --revision 6_5 --local-dir UNA-dolphin-2.6-mistral-7b-dpo-laser-exl2-6_5 --local-dir-use-symlinks False
```
