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tensorblock
/
gemma-2b-coder-GGUF

Text Generation
GGUF
code
Generated from Trainer
coding
gemma
TensorBlock
GGUF
Model card Files Community
gemma-2b-coder-GGUF
File size: 6,666 Bytes 
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---
tags:
- generated_from_trainer
- code
- coding
- gemma
- TensorBlock
- GGUF
license_name: gemma-terms-of-use
license_link: https://ai.google.dev/gemma/terms
language:
- code
thumbnail: https://huggingface.co/mrm8488/gemma-2b-coder/resolve/main/logo.png
datasets:
- HuggingFaceH4/CodeAlpaca_20K
pipeline_tag: text-generation
base_model: MAISAAI/gemma-2b-coder
model-index:
- name: gemma-2b-coder
  results: []
---

<div style="width: auto; margin-left: auto; margin-right: auto">
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## MAISAAI/gemma-2b-coder - GGUF

This repo contains GGUF format model files for [MAISAAI/gemma-2b-coder](https://huggingface.co/MAISAAI/gemma-2b-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).

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<table border="1" cellspacing="0" cellpadding="10">
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</table>
## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [gemma-2b-coder-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q2_K.gguf) | Q2_K | 1.158 GB | smallest, significant quality loss - not recommended for most purposes |
| [gemma-2b-coder-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q3_K_S.gguf) | Q3_K_S | 1.288 GB | very small, high quality loss |
| [gemma-2b-coder-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q3_K_M.gguf) | Q3_K_M | 1.384 GB | very small, high quality loss |
| [gemma-2b-coder-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q3_K_L.gguf) | Q3_K_L | 1.466 GB | small, substantial quality loss |
| [gemma-2b-coder-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q4_0.gguf) | Q4_0 | 1.551 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [gemma-2b-coder-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q4_K_S.gguf) | Q4_K_S | 1.560 GB | small, greater quality loss |
| [gemma-2b-coder-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q4_K_M.gguf) | Q4_K_M | 1.630 GB | medium, balanced quality - recommended |
| [gemma-2b-coder-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q5_0.gguf) | Q5_0 | 1.799 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [gemma-2b-coder-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q5_K_S.gguf) | Q5_K_S | 1.799 GB | large, low quality loss - recommended |
| [gemma-2b-coder-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q5_K_M.gguf) | Q5_K_M | 1.840 GB | large, very low quality loss - recommended |
| [gemma-2b-coder-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q6_K.gguf) | Q6_K | 2.062 GB | very large, extremely low quality loss |
| [gemma-2b-coder-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-2b-coder-GGUF/blob/main/gemma-2b-coder-Q8_0.gguf) | Q8_0 | 2.669 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/gemma-2b-coder-GGUF --include "gemma-2b-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/gemma-2b-coder-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```