---
pipeline_tag: text-generation
inference: true
widget:
- text: 'def print_hello_world():'
example_title: Hello world
group: Python
license: bigcode-openrail-m
datasets:
- bigcode/the-stack-dedup
metrics:
- code_eval
library_name: transformers
tags:
- code
- TensorBlock
- GGUF
base_model: bigcode/tiny_starcoder_py
model-index:
- name: Tiny-StarCoder-Py
results:
- task:
type: text-generation
dataset:
name: HumanEval
type: openai_humaneval
metrics:
- type: pass@1
value: 7.84%
name: pass@1
verified: false
---
## bigcode/tiny_starcoder_py - GGUF
This repo contains GGUF format model files for [bigcode/tiny_starcoder_py](https://huggingface.co/bigcode/tiny_starcoder_py).
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 |
| -------- | ---------- | --------- | ----------- |
| [tiny_starcoder_py-Q2_K.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q2_K.gguf) | Q2_K | 0.097 GB | smallest, significant quality loss - not recommended for most purposes |
| [tiny_starcoder_py-Q3_K_S.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q3_K_S.gguf) | Q3_K_S | 0.103 GB | very small, high quality loss |
| [tiny_starcoder_py-Q3_K_M.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q3_K_M.gguf) | Q3_K_M | 0.112 GB | very small, high quality loss |
| [tiny_starcoder_py-Q3_K_L.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q3_K_L.gguf) | Q3_K_L | 0.118 GB | small, substantial quality loss |
| [tiny_starcoder_py-Q4_0.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q4_0.gguf) | Q4_0 | 0.117 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [tiny_starcoder_py-Q4_K_S.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q4_K_S.gguf) | Q4_K_S | 0.118 GB | small, greater quality loss |
| [tiny_starcoder_py-Q4_K_M.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q4_K_M.gguf) | Q4_K_M | 0.125 GB | medium, balanced quality - recommended |
| [tiny_starcoder_py-Q5_0.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q5_0.gguf) | Q5_0 | 0.131 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [tiny_starcoder_py-Q5_K_S.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q5_K_S.gguf) | Q5_K_S | 0.131 GB | large, low quality loss - recommended |
| [tiny_starcoder_py-Q5_K_M.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q5_K_M.gguf) | Q5_K_M | 0.136 GB | large, very low quality loss - recommended |
| [tiny_starcoder_py-Q6_K.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q6_K.gguf) | Q6_K | 0.146 GB | very large, extremely low quality loss |
| [tiny_starcoder_py-Q8_0.gguf](https://huggingface.co/tensorblock/tiny_starcoder_py-GGUF/blob/main/tiny_starcoder_py-Q8_0.gguf) | Q8_0 | 0.182 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/tiny_starcoder_py-GGUF --include "tiny_starcoder_py-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/tiny_starcoder_py-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```