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33x-coder-GGUF

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33x-coder-GGUF
File size: 6,318 Bytes
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---
language:
- en
metrics:
- code_eval
library_name: transformers
tags:
- Code Generation
- TensorBlock
- GGUF
datasets:
- andersonbcdefg/synthetic_retrieval_tasks
- ise-uiuc/Magicoder-Evol-Instruct-110K
license: apache-2.0
base_model: senseable/33x-coder
---

<div style="width: auto; margin-left: auto; margin-right: auto">
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## senseable/33x-coder - GGUF

This repo contains GGUF format model files for [senseable/33x-coder](https://huggingface.co/senseable/33x-coder).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
  <tr>
    <th colspan="2" style="font-size: 25px;">Forge</th>
  </tr>
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      <img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/>
    </th>
  </tr>
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    <th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
  </tr>
  <tr>
    <th colspan="2">
      <a href="https://github.com/TensorBlock/forge" target="_blank" style="
        display: inline-block;
        padding: 8px 16px;
        background-color: #FF7F50;
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        text-decoration: none;
        border-radius: 6px;
        font-weight: bold;
        font-family: sans-serif;
      ">🚀 Try it now! 🚀</a>
    </th>
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    <th style="font-size: 25px;">Awesome MCP Servers</th>
    <th style="font-size: 25px;">TensorBlock Studio</th>
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    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
    <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th>
  </tr>
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    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
    <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
  </tr>
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      <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
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        font-weight: bold;
        font-family: sans-serif;
      ">👀 See what we built 👀</a>
    </th>
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      <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
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        font-weight: bold;
        font-family: sans-serif;
      ">👀 See what we built 👀</a>
    </th>
  </tr>
</table>
## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [33x-coder-Q2_K.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q2_K.gguf) | Q2_K | 12.356 GB | smallest, significant quality loss - not recommended for most purposes |
| [33x-coder-Q3_K_S.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q3_K_S.gguf) | Q3_K_S | 14.422 GB | very small, high quality loss |
| [33x-coder-Q3_K_M.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q3_K_M.gguf) | Q3_K_M | 16.092 GB | very small, high quality loss |
| [33x-coder-Q3_K_L.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q3_K_L.gguf) | Q3_K_L | 17.560 GB | small, substantial quality loss |
| [33x-coder-Q4_0.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q4_0.gguf) | Q4_0 | 18.819 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [33x-coder-Q4_K_S.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q4_K_S.gguf) | Q4_K_S | 18.943 GB | small, greater quality loss |
| [33x-coder-Q4_K_M.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q4_K_M.gguf) | Q4_K_M | 19.941 GB | medium, balanced quality - recommended |
| [33x-coder-Q5_0.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q5_0.gguf) | Q5_0 | 22.958 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [33x-coder-Q5_K_S.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q5_K_S.gguf) | Q5_K_S | 22.958 GB | large, low quality loss - recommended |
| [33x-coder-Q5_K_M.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q5_K_M.gguf) | Q5_K_M | 23.536 GB | large, very low quality loss - recommended |
| [33x-coder-Q6_K.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q6_K.gguf) | Q6_K | 27.356 GB | very large, extremely low quality loss |
| [33x-coder-Q8_0.gguf](https://huggingface.co/tensorblock/33x-coder-GGUF/blob/main/33x-coder-Q8_0.gguf) | Q8_0 | 35.431 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/33x-coder-GGUF --include "33x-coder-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/33x-coder-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```