Text Generation
Transformers
Inference Endpoints
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measurement.json
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---
license: other
license_name: deepseek
datasets:
- ise-uiuc/Magicoder-OSS-Instruct-75K
library_name: transformers
pipeline_tag: text-generation
quantized_by: bartowski
---
## Exllama v2 Quantizations of Magicoder-DS-6.7B
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.
# The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
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/ise-uiuc/Magicoder-DS-6.7B/
No GQA - VRAM requirements will be higher
| Branch | Bits | lm_head bits | Size (4k) | Size (16k) | Description |
| -------------------------------------------------------------- | ---- | ------------ | --------- | ---------- | ----------- |
| [8_0](https://huggingface.co/Bartowski/Magicoder-DS-6.7B-exl2/tree/8_0) | 8.0 | 8.0 | 9.4 GB | 15.6 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| [6_5](https://huggingface.co/Bartowski/Magicoder-DS-6.7B-exl2/tree/6_5) | 6.5 | 8.0 | 8.6 GB | 14.8 GB | Near unquantized performance at vastly reduced size, **recommended**. |
| [5_0](https://huggingface.co/Bartowski/Magicoder-DS-6.7B-exl2/tree/5_0) | 5.0 | 6.0 | 7.2 GB | 13.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards with 4k context. |
| [4_25](https://huggingface.co/Bartowski/Magicoder-DS-6.7B-exl2/tree/4_25) | 4.25 | 6.0 | 6.5 GB | 12.7 GB | GPTQ equivalent bits per weight. |
| [3_5](https://huggingface.co/Bartowski/Magicoder-DS-6.7B-exl2/tree/3_5) | 3.5 | 6.0 | 5.9 GB | 12.1 GB | Lower quality, not recommended. |
VRAM requirements listed for both 4k context and 16k context since without GQA the differences are massive (6.2 GB)
## Download instructions
With git:
```shell
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Magicoder-DS-6.7B-exl2 Magicoder-DS-6.7B-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 `Magicoder-DS-6.7B-exl2`:
```shell
mkdir Magicoder-DS-6.7B-exl2
huggingface-cli download bartowski/Magicoder-DS-6.7B-exl2 --local-dir Magicoder-DS-6.7B-exl2 --local-dir-use-symlinks False
```
To download from a different branch, add the `--revision` parameter:
```shell
mkdir Magicoder-DS-6.7B-exl2-6_5
huggingface-cli download bartowski/Magicoder-DS-6.7B-exl2 --revision 6_5 --local-dir Magicoder-DS-6.7B-exl2-6_5 --local-dir-use-symlinks False
```