---
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
- argilla/ultrafeedback-binarized-preferences-cleaned
language:
- en
license: apache-2.0
quantized_by: bartowski
pipeline_tag: text-generation
---

## Exllama v2 Quantizations of 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.

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/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser/

Model Size: 7b

| Branch | Bits | lm_head bits | Dataset | Size | Description |
| ----- | ---- | ------- | ------- | ------ | ------------ |
| [8_0](https://huggingface.co/Bartowski/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/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/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/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/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/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 `dolphin-2.6-mistral-7b-dpo-laser-exl2`:

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