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---
language:
- en
- ja
library_name: transformers
pipeline_tag: text-generation
license: llama2
model_type: llama
tags:
- TensorBlock
- GGUF
base_model: tokyotech-llm/Swallow-7b-instruct-hf
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<div style="display: flex; flex-direction: column; align-items: flex-start;">
<p style="margin-top: 0.5em; margin-bottom: 0em;">
Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
</p>
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## tokyotech-llm/Swallow-7b-instruct-hf - GGUF
This repo contains GGUF format model files for [tokyotech-llm/Swallow-7b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-7b-instruct-hf).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
## Prompt template
```
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Swallow-7b-instruct-hf-Q2_K.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q2_K.gguf) | Q2_K | 2.408 GB | smallest, significant quality loss - not recommended for most purposes |
| [Swallow-7b-instruct-hf-Q3_K_S.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q3_K_S.gguf) | Q3_K_S | 2.799 GB | very small, high quality loss |
| [Swallow-7b-instruct-hf-Q3_K_M.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q3_K_M.gguf) | Q3_K_M | 3.125 GB | very small, high quality loss |
| [Swallow-7b-instruct-hf-Q3_K_L.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q3_K_L.gguf) | Q3_K_L | 3.404 GB | small, substantial quality loss |
| [Swallow-7b-instruct-hf-Q4_0.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q4_0.gguf) | Q4_0 | 3.622 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Swallow-7b-instruct-hf-Q4_K_S.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q4_K_S.gguf) | Q4_K_S | 3.651 GB | small, greater quality loss |
| [Swallow-7b-instruct-hf-Q4_K_M.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q4_K_M.gguf) | Q4_K_M | 3.860 GB | medium, balanced quality - recommended |
| [Swallow-7b-instruct-hf-Q5_0.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q5_0.gguf) | Q5_0 | 4.397 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Swallow-7b-instruct-hf-Q5_K_S.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q5_K_S.gguf) | Q5_K_S | 4.397 GB | large, low quality loss - recommended |
| [Swallow-7b-instruct-hf-Q5_K_M.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q5_K_M.gguf) | Q5_K_M | 4.519 GB | large, very low quality loss - recommended |
| [Swallow-7b-instruct-hf-Q6_K.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q6_K.gguf) | Q6_K | 5.220 GB | very large, extremely low quality loss |
| [Swallow-7b-instruct-hf-Q8_0.gguf](https://huggingface.co/tensorblock/Swallow-7b-instruct-hf-GGUF/tree/main/Swallow-7b-instruct-hf-Q8_0.gguf) | Q8_0 | 6.760 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/Swallow-7b-instruct-hf-GGUF --include "Swallow-7b-instruct-hf-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/Swallow-7b-instruct-hf-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
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