File size: 6,955 Bytes

---
datasets:
- wikipedia
language:
- zh
- en
tags:
- chinese
- english
- TensorBlock
- GGUF
inference:
  parameters:
    max_new_tokens: 50
    do_sample: true
widget:
- text: 粉圓，在珍珠奶茶中也稱波霸或珍珠，是一種
pipeline_tag: text-generation
base_model: p208p2002/llama-chinese-81M
---

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## p208p2002/llama-chinese-81M - GGUF

This repo contains GGUF format model files for [p208p2002/llama-chinese-81M](https://huggingface.co/p208p2002/llama-chinese-81M).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985).

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## Prompt template

```
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [llama-chinese-81M-Q2_K.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q2_K.gguf) | Q2_K | 0.037 GB | smallest, significant quality loss - not recommended for most purposes |
| [llama-chinese-81M-Q3_K_S.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q3_K_S.gguf) | Q3_K_S | 0.042 GB | very small, high quality loss |
| [llama-chinese-81M-Q3_K_M.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q3_K_M.gguf) | Q3_K_M | 0.045 GB | very small, high quality loss |
| [llama-chinese-81M-Q3_K_L.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q3_K_L.gguf) | Q3_K_L | 0.047 GB | small, substantial quality loss |
| [llama-chinese-81M-Q4_0.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q4_0.gguf) | Q4_0 | 0.051 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [llama-chinese-81M-Q4_K_S.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q4_K_S.gguf) | Q4_K_S | 0.051 GB | small, greater quality loss |
| [llama-chinese-81M-Q4_K_M.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q4_K_M.gguf) | Q4_K_M | 0.052 GB | medium, balanced quality - recommended |
| [llama-chinese-81M-Q5_0.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q5_0.gguf) | Q5_0 | 0.059 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [llama-chinese-81M-Q5_K_S.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q5_K_S.gguf) | Q5_K_S | 0.059 GB | large, low quality loss - recommended |
| [llama-chinese-81M-Q5_K_M.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q5_K_M.gguf) | Q5_K_M | 0.060 GB | large, very low quality loss - recommended |
| [llama-chinese-81M-Q6_K.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q6_K.gguf) | Q6_K | 0.067 GB | very large, extremely low quality loss |
| [llama-chinese-81M-Q8_0.gguf](https://huggingface.co/tensorblock/p208p2002_llama-chinese-81M-GGUF/blob/main/llama-chinese-81M-Q8_0.gguf) | Q8_0 | 0.087 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/p208p2002_llama-chinese-81M-GGUF --include "llama-chinese-81M-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/p208p2002_llama-chinese-81M-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```