alignment-handbook generated_from_trainer juanako mistral UNA text-generation dataset:HuggingFaceH4/ultrafeedback_binarized license:apache-2.0 model-index region:us
---
datasets:
- HuggingFaceH4/ultrafeedback_binarized
license: apache-2.0
pipeline_tag: text-generation
tags:
- alignment-handbook
- generated_from_trainer
- juanako
- mistral
- UNA
quantized_by: bartowski
model-index:
- name: juanako-7b-UNA
  results:
  - task:
      type: text-generation
      name: TruthfulQA (MC2)
    dataset:
      name: truthful_qa
      type: text-generation
      config: multiple_choice
      split: validation
    metrics:
    - type: accuracy
      value: 65.13
      verified: true
  - task:
      type: text-generation
      name: ARC-Challenge
    dataset:
      name: ai2_arc
      type: text-generation
      config: ARC-Challenge
      split: test
    metrics:
    - type: accuracy
      value: 68.17
      verified: true
  - task:
      type: text-generation
      name: HellaSwag
    dataset:
      name: Rowan/hellaswag
      type: text-generation
      split: test
    metrics:
    - type: accuracy
      value: 85.34
      verified: true
    - type: accuracy
      value: 83.57
  - task:
      type: text-generation
      name: Winogrande
    dataset:
      name: winogrande
      type: text-generation
      config: winogrande_debiased
      split: test
    metrics:
    - type: accuracy
      value: 78.85
      verified: true
  - task:
      type: text-generation
      name: MMLU
    dataset:
      name: cais/mmlu
      type: text-generation
      config: all
      split: test
    metrics:
    - type: accuracy
      value: 62.47
      verified: true
  - task:
      type: text-generation
      name: DROP
    dataset:
      name: drop
      type: text-generation
      split: validation
    metrics:
    - type: accuracy
      value: 38.74
      verified: true
  - task:
      type: text-generation
      name: PubMedQA
    dataset:
      name: bigbio/pubmed_qa
      type: text-generation
      config: pubmed_qa_artificial_bigbio_qa
      split: validation
    metrics:
    - type: accuracy
      value: 76.0
---

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

Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.10">turboderp's ExLlamaV2 v0.0.10</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-UNA
 
<a href="https://huggingface.co/bartowski/juanako-7b-UNA-exl2/tree/4_0">4.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-UNA-exl2/tree/5_0">5.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-UNA-exl2/tree/6_0">6.0 bits per weight</a>
 
<a href="https://huggingface.co/bartowski/juanako-7b-UNA-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-UNA-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-UNA-exl2`:

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

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

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