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---
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
```
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