---
library_name: transformers
tags:
- TensorBlock
- GGUF
base_model: jdchang/norm_test
---

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## jdchang/norm_test - GGUF

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        Join our Discord to learn more about what we're building ↗
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This repo contains GGUF format model files for [jdchang/norm_test](https://huggingface.co/jdchang/norm_test).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).

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## Prompt template

```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [norm_test-Q2_K.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q2_K.gguf) | Q2_K | 5.770 GB | smallest, significant quality loss - not recommended for most purposes |
| [norm_test-Q3_K_S.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q3_K_S.gguf) | Q3_K_S | 6.660 GB | very small, high quality loss |
| [norm_test-Q3_K_M.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q3_K_M.gguf) | Q3_K_M | 7.339 GB | very small, high quality loss |
| [norm_test-Q3_K_L.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q3_K_L.gguf) | Q3_K_L | 7.925 GB | small, substantial quality loss |
| [norm_test-Q4_0.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q4_0.gguf) | Q4_0 | 8.518 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [norm_test-Q4_K_S.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q4_K_S.gguf) | Q4_K_S | 8.573 GB | small, greater quality loss |
| [norm_test-Q4_K_M.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q4_K_M.gguf) | Q4_K_M | 8.988 GB | medium, balanced quality - recommended |
| [norm_test-Q5_0.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q5_0.gguf) | Q5_0 | 10.267 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [norm_test-Q5_K_S.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q5_K_S.gguf) | Q5_K_S | 10.267 GB | large, low quality loss - recommended |
| [norm_test-Q5_K_M.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q5_K_M.gguf) | Q5_K_M | 10.509 GB | large, very low quality loss - recommended |
| [norm_test-Q6_K.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q6_K.gguf) | Q6_K | 12.125 GB | very large, extremely low quality loss |
| [norm_test-Q8_0.gguf](https://huggingface.co/tensorblock/jdchang_norm_test-GGUF/blob/main/norm_test-Q8_0.gguf) | Q8_0 | 15.702 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/jdchang_norm_test-GGUF --include "norm_test-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/jdchang_norm_test-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```