---
license: apache-2.0
tags:
- alignment-handbook
- generated_from_trainer
- juanako
- mistral
- UNA
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: juanako-7b-UNA
results:
- task:
type: text-generation
name: TruthfulQA (MC2)
dataset:
type: text-generation
name: truthful_qa
config: multiple_choice
split: validation
metrics:
- type: accuracy
value: 65.13
verified: true
- task:
type: text-generation
name: ARC-Challenge
dataset:
type: text-generation
name: ai2_arc
config: ARC-Challenge
split: test
metrics:
- type: accuracy
value: 68.17
verified: true
- task:
type: text-generation
name: HellaSwag
dataset:
type: text-generation
name: Rowan/hellaswag
split: test
metrics:
- type: accuracy
value: 85.34
verified: true
- task:
type: text-generation
name: Winogrande
dataset:
type: text-generation
name: winogrande
config: winogrande_debiased
split: test
metrics:
- type: accuracy
value: 78.85
verified: true
- task:
type: text-generation
name: MMLU
dataset:
type: text-generation
name: cais/mmlu
config: all
split: test
metrics:
- type: accuracy
value: 62.47
verified: true
- task:
type: text-generation
name: PiQA
dataset:
type: text-generation
name: piqa
split: test
metrics:
- type: accuracy
value: 83.57
- task:
type: text-generation
name: DROP
dataset:
type: text-generation
name: drop
split: validation
metrics:
- type: accuracy
value: 38.74
verified: true
- task:
type: text-generation
name: PubMedQA
dataset:
type: text-generation
name: bigbio/pubmed_qa
config: pubmed_qa_artificial_bigbio_qa
split: validation
metrics:
- type: accuracy
value: 76.0
quantized_by: bartowski
pipeline_tag: text-generation
---
## Exllama v2 Quantizations of juanako-7b-UNA
Using turboderp's ExLlamaV2 v0.0.10 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
4.0 bits per weight
5.0 bits per weight
6.0 bits per weight
8.0 bits per weight
## 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
```