---
tags:
- autotrain
- text-generation-inference
- text-generation
- peft
- TensorBlock
- GGUF
library_name: transformers
base_model: neural-coder/gorilla-finetuned
widget:
- messages:
  - role: user
    content: What is your favorite condiment?
license: apache-2.0
---

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## neural-coder/gorilla-finetuned - GGUF

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    <a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Join our Discord to learn more about what we're building ↗
    </a>
</div>

This repo contains GGUF format model files for [neural-coder/gorilla-finetuned](https://huggingface.co/neural-coder/gorilla-finetuned).

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

```
<｜begin▁of▁sentence｜>{system_prompt}### Instruction:
{prompt}
### Response:
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [gorilla-finetuned-Q2_K.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q2_K.gguf) | Q2_K | 2.707 GB | smallest, significant quality loss - not recommended for most purposes |
| [gorilla-finetuned-Q3_K_S.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q3_K_S.gguf) | Q3_K_S | 3.126 GB | very small, high quality loss |
| [gorilla-finetuned-Q3_K_M.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q3_K_M.gguf) | Q3_K_M | 3.449 GB | very small, high quality loss |
| [gorilla-finetuned-Q3_K_L.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q3_K_L.gguf) | Q3_K_L | 3.734 GB | small, substantial quality loss |
| [gorilla-finetuned-Q4_0.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q4_0.gguf) | Q4_0 | 3.987 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [gorilla-finetuned-Q4_K_S.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q4_K_S.gguf) | Q4_K_S | 4.012 GB | small, greater quality loss |
| [gorilla-finetuned-Q4_K_M.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q4_K_M.gguf) | Q4_K_M | 4.210 GB | medium, balanced quality - recommended |
| [gorilla-finetuned-Q5_0.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q5_0.gguf) | Q5_0 | 4.797 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [gorilla-finetuned-Q5_K_S.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q5_K_S.gguf) | Q5_K_S | 4.797 GB | large, low quality loss - recommended |
| [gorilla-finetuned-Q5_K_M.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q5_K_M.gguf) | Q5_K_M | 4.912 GB | large, very low quality loss - recommended |
| [gorilla-finetuned-Q6_K.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q6_K.gguf) | Q6_K | 5.657 GB | very large, extremely low quality loss |
| [gorilla-finetuned-Q8_0.gguf](https://huggingface.co/tensorblock/neural-coder_gorilla-finetuned-GGUF/blob/main/gorilla-finetuned-Q8_0.gguf) | Q8_0 | 7.326 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/neural-coder_gorilla-finetuned-GGUF --include "gorilla-finetuned-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/neural-coder_gorilla-finetuned-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```