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---
tags:
- quantized
- chatml
datasets:
- allenai/ai2_arc
- allenai/ultrafeedback_binarized_cleaned
- argilla/distilabel-intel-orca-dpo-pairs
- jondurbin/airoboros-3.2
- codeparrot/apps
- facebook/belebele
- bluemoon-fandom-1-1-rp-cleaned
- boolq
- camel-ai/biology
- camel-ai/chemistry
- camel-ai/math
- camel-ai/physics
- jondurbin/contextual-dpo-v0.1
- jondurbin/gutenberg-dpo-v0.1
- jondurbin/py-dpo-v0.1
- jondurbin/truthy-dpo-v0.1
- LDJnr/Capybara
- jondurbin/cinematika-v0.1
- WizardLM/WizardLM_evol_instruct_70k
- glaiveai/glaive-function-calling-v2
- jondurbin/gutenberg-dpo-v0.1
- grimulkan/LimaRP-augmented
- lmsys/lmsys-chat-1m
- ParisNeo/lollms_aware_dataset
- TIGER-Lab/MathInstruct
- Muennighoff/natural-instructions
- openbookqa
- kingbri/PIPPA-shareGPT
- piqa
- Vezora/Tested-22k-Python-Alpaca
- ropes
- cakiki/rosetta-code
- Open-Orca/SlimOrca
- b-mc2/sql-create-context
- squad_v2
- mattpscott/airoboros-summarization
- migtissera/Synthia-v1.3
- unalignment/toxic-dpo-v0.2
- WhiteRabbitNeo/WRN-Chapter-1
- WhiteRabbitNeo/WRN-Chapter-2
- winogrande
base_model: 01-ai/yi-34b-200k
model_type: mistral
pipeline_tag: text-generation
inference: false
license: apache-2.0
---
# jondurbin/bagel-34b-v0.5 Exl2
- Model creator: [jondurbin](https://huggingface.co/jondurbin)
- Original model: [bagel-34b-v0.5](https://huggingface.co/jondurbin/bagel-34b-v0.5)
## Model Summary
This is a fine-tune of the updated yi-34b-200k with better long-context support.
See [bagel](https://github.com/jondurbin/bagel) for additional details on the datasets.
The DPO version is available [here](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.5)
## How to Use
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.14">turboderp's ExLlamaV2 v0.0.14</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
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/jondurbin/bagel-34b-v0.5
| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
| ------ | ---- | ------------ | ---- | ---- | ---- | ----------- |
| [6_5](https://huggingface.co/suparious/bagel-34b-v0.5-exl2/tree/6_5) | 6.5 | 8.0 | 28.9 GB | 31.6 GB | 35.6 GB | Near unquantized performance at vastly reduced size, **recommended**. |
| [4_25](https://huggingface.co/suparious/bagel-34b-v0.5-exl2/tree/4_25) | 4.25 | 6.0 | 19.5 GB | 22.2 GB | 26.2 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| [3_5](https://huggingface.co/suparious/bagel-34b-v0.5-exl2/tree/3_5) | 3.5 | 6.0 | 16.5 GB | 19.2 GB | 23.2 GB | Lower quality, only use if you have to. |
| [3_0](https://huggingface.co/suparious/bagel-34b-v0.5-exl2/tree/3_0) | 3.0 | 6.0 | 14.3 GB | 17.0 GB | 21.0 GB | Very low quality, usable with 16gb of VRAM. |
## Download instructions
With git:
```shell
git clone --single-branch --branch 6_5 https://huggingface.co/suparious/bagel-34b-v0.5-exl2 bagel-34b-v0.5-exl2-6_5
```
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 `bagel-34b-v0.5-exl2`:
```shell
mkdir bagel-34b-v0.5-exl2
huggingface-cli download suparious/bagel-34b-v0.5-exl2 --local-dir bagel-34b-v0.5-exl2 --local-dir-use-symlinks False
```
To download from a different branch, add the `--revision` parameter:
Linux:
```shell
mkdir bagel-34b-v0.5-exl2-6_5
huggingface-cli download suparious/bagel-34b-v0.5-exl2 --revision 6_5 --local-dir bagel-34b-v0.5-exl2-6_5 --local-dir-use-symlinks False
```
Windows (which apparently doesn't like _ in folders sometimes?):
```shell
mkdir bagel-34b-v0.5-exl2-6.5
huggingface-cli download suparious/bagel-34b-v0.5-exl2 --revision 6_5 --local-dir bagel-34b-v0.5-exl2-6.5 --local-dir-use-symlinks False
``` |