gguf uncensored TensorBlock GGUF dataset:ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered dataset:kaiokendev/SuperCOT-dataset dataset:neulab/conala dataset:yahma/alpaca-cleaned dataset:QingyiSi/Alpaca-CoT dataset:timdettmers/guanaco-33b dataset:JosephusCheung/GuanacoDataset base_model:Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b base_model:quantized:Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b license:other endpoints_compatible region:us
---
base_model: Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b
datasets:
- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
- kaiokendev/SuperCOT-dataset
- neulab/conala
- yahma/alpaca-cleaned
- QingyiSi/Alpaca-CoT
- timdettmers/guanaco-33b
- JosephusCheung/GuanacoDataset
license: other
tags:
- uncensored
- TensorBlock
- GGUF
---

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<div style="display: flex; justify-content: space-between; width: 100%;">
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            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b - GGUF

This repo contains GGUF format model files for [Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b](https://huggingface.co/Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b).

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).

<div style="text-align: left; margin: 20px 0;">
    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Run them on the TensorBlock client using your local machine ↗
    </a>
</div>

## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q2_K.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q2_K.gguf) | Q2_K | 11.221 GB | smallest, significant quality loss - not recommended for most purposes |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_S.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_S.gguf) | Q3_K_S | 13.098 GB | very small, high quality loss |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_M.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_M.gguf) | Q3_K_M | 14.693 GB | very small, high quality loss |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_L.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q3_K_L.gguf) | Q3_K_L | 16.093 GB | small, substantial quality loss |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_0.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_0.gguf) | Q4_0 | 17.095 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_K_S.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_K_S.gguf) | Q4_K_S | 17.213 GB | small, greater quality loss |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_K_M.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q4_K_M.gguf) | Q4_K_M | 18.274 GB | medium, balanced quality - recommended |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_0.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_0.gguf) | Q5_0 | 20.857 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_K_S.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_K_S.gguf) | Q5_K_S | 20.857 GB | large, low quality loss - recommended |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_K_M.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q5_K_M.gguf) | Q5_K_M | 21.464 GB | large, very low quality loss - recommended |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q6_K.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q6_K.gguf) | Q6_K | 24.854 GB | very large, extremely low quality loss |
| [WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q8_0.gguf](https://huggingface.co/tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF/blob/main/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-Q8_0.gguf) | Q8_0 | 32.191 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/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF --include "WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-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/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
