---
base_model: fblgit/zephyr-lora-dpo-b1
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: juanako-7b-v1
  results: []
license: artistic-2.0
quantized_by: bartowski
pipeline_tag: text-generation
---

## Exllama v2 Quantizations of juanako-7b-v1

Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.9">turboderp's ExLlamaV2 v0.0.9</a> for quantization.

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

Conversion was done using wikitext-103-raw-v1-test.parquet as calibration dataset.

Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.

Original model: https://huggingface.co/fblgit/juanako-7b-v1
 
<a href="https://huggingface.co/bartowski/juanako-7b-v1-exl2/tree/4_0">4.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-v1-exl2/tree/5_0">5.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-v1-exl2/tree/6_0">6.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-v1-exl2/tree/8_0">8.0 bits per weight</a>

## Download instructions

With git:

```shell
git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/juanako-7b-v1-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 `juanako-7b-v1-exl2`:

```shell
mkdir juanako-7b-v1-exl2
huggingface-cli download bartowski/juanako-7b-v1-exl2 --local-dir juanako-7b-v1-exl2 --local-dir-use-symlinks False
```

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

```shell
mkdir juanako-7b-v1-exl2
huggingface-cli download bartowski/juanako-7b-v1-exl2 --revision 4_0 --local-dir juanako-7b-v1-exl2 --local-dir-use-symlinks False
```