---
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
---

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## 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).


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## 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'
```