---
pipeline_tag: text-generation
inference:
parameters:
temperature: 0.2
top_p: 0.95
widget:
- text: 'def print_hello_world():'
example_title: Hello world
group: Python
datasets:
- bigcode/the-stack-v2-train
license: bigcode-openrail-m
library_name: transformers
tags:
- code
- TensorBlock
- GGUF
base_model: bigcode/starcoder2-15b
model-index:
- name: starcoder2-15b
results:
- task:
type: text-generation
dataset:
name: CruxEval-I
type: cruxeval-i
metrics:
- type: pass@1
value: 48.1
- task:
type: text-generation
dataset:
name: DS-1000
type: ds-1000
metrics:
- type: pass@1
value: 33.8
- task:
type: text-generation
dataset:
name: GSM8K (PAL)
type: gsm8k-pal
metrics:
- type: accuracy
value: 65.1
- task:
type: text-generation
dataset:
name: HumanEval+
type: humanevalplus
metrics:
- type: pass@1
value: 37.8
- task:
type: text-generation
dataset:
name: HumanEval
type: humaneval
metrics:
- type: pass@1
value: 46.3
- task:
type: text-generation
dataset:
name: RepoBench-v1.1
type: repobench-v1.1
metrics:
- type: edit-smiliarity
value: 74.08
---
## bigcode/starcoder2-15b - GGUF
This repo contains GGUF format model files for [bigcode/starcoder2-15b](https://huggingface.co/bigcode/starcoder2-15b).
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 |
| -------- | ---------- | --------- | ----------- |
| [starcoder2-15b-Q2_K.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q2_K.gguf) | Q2_K | 5.768 GB | smallest, significant quality loss - not recommended for most purposes |
| [starcoder2-15b-Q3_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q3_K_S.gguf) | Q3_K_S | 6.507 GB | very small, high quality loss |
| [starcoder2-15b-Q3_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q3_K_M.gguf) | Q3_K_M | 7.492 GB | very small, high quality loss |
| [starcoder2-15b-Q3_K_L.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q3_K_L.gguf) | Q3_K_L | 8.350 GB | small, substantial quality loss |
| [starcoder2-15b-Q4_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q4_0.gguf) | Q4_0 | 8.443 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [starcoder2-15b-Q4_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q4_K_S.gguf) | Q4_K_S | 8.532 GB | small, greater quality loss |
| [starcoder2-15b-Q4_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q4_K_M.gguf) | Q4_K_M | 9.183 GB | medium, balanced quality - recommended |
| [starcoder2-15b-Q5_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q5_0.gguf) | Q5_0 | 10.265 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [starcoder2-15b-Q5_K_S.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q5_K_S.gguf) | Q5_K_S | 10.265 GB | large, low quality loss - recommended |
| [starcoder2-15b-Q5_K_M.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q5_K_M.gguf) | Q5_K_M | 10.646 GB | large, very low quality loss - recommended |
| [starcoder2-15b-Q6_K.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q6_K.gguf) | Q6_K | 12.201 GB | very large, extremely low quality loss |
| [starcoder2-15b-Q8_0.gguf](https://huggingface.co/tensorblock/starcoder2-15b-GGUF/blob/main/starcoder2-15b-Q8_0.gguf) | Q8_0 | 15.800 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/starcoder2-15b-GGUF --include "starcoder2-15b-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/starcoder2-15b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```