README.md

---
inference: false
license: other
datasets:
- gozfarb/ShareGPT_Vicuna_unfiltered
---

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# Aeala's VicUnlocked Alpaca 65B QLoRA GGML

These files are GGML format model files for [Aeala's VicUnlocked Alpaca 65B QLoRA](https://huggingface.co/Aeala/VicUnlocked-alpaca-65b-QLoRA).

GGML files are for CPU + GPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp) and libraries and UIs which support this format, such as:
* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
* [KoboldCpp](https://github.com/LostRuins/koboldcpp)
* [ParisNeo/GPT4All-UI](https://github.com/ParisNeo/gpt4all-ui)
* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
* [ctransformers](https://github.com/marella/ctransformers)

## Other repositories available

* [4-bit GPTQ models for GPU inference](https://huggingface.co/Aeala/VicUnlocked-alpaca-65b-4bit)
* [4-bit, 5-bit, and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/VicUnlocked-alpaca-65B-QLoRA-GGML)
* [Original unquantised fp16 model in HF format](https://huggingface.co/TheBloke/VicUnlocked-alpaca-65B-QLoRA-fp16)

## THE FILES IN MAIN BRANCH REQUIRES LATEST LLAMA.CPP (May 19th 2023 - commit 2d5db48)!

llama.cpp recently made another breaking change to its quantisation methods - https://github.com/ggerganov/llama.cpp/pull/1508

I have quantised the GGML files in this repo with the latest version. Therefore you will require llama.cpp compiled on May 19th or later (commit `2d5db48` or later) to use them.

## Provided files
| Name | Quant method | Bits | Size | RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
| VicUnlocked-Alpaca-65B.ggmlv3.q4_0.bin | q4_0 | 4 | 36.73 GB | 39.23 GB | 4-bit. |
| VicUnlocked-Alpaca-65B.ggmlv3.q4_1.bin | q4_1 | 4 | 40.81 GB | 43.31 GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
| VicUnlocked-Alpaca-65B.ggmlv3.q5_0.bin | q5_0 | 5 | 44.89 GB | 47.39 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
| VicUnlocked-Alpaca-65B.ggmlv3.q5_1.bin | q5_1 | 5 | 48.97 GB | 51.47 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
| VicUnlocked-Alpaca-65B.ggmlv3.q8_0.bin | q8_0 | 8 | 69.37 GB | 71.87 GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for most use cases. |

### q8_0 file requires expansion from archive

**Note:** HF does not support uploading files larger than 50GB. Therefore I have uploaded the q8_0 file in a multi-part ZIP file. The ZIP is not compressed, it is just storing the .bin file in two parts.

To decompress it, please download
* `VicUnlocked-Alpaca-65B.ggmlv3.q8_0.zip`
* `VicUnlocked-Alpaca-65B.ggmlv3.q8_0.z01`

and extract the .zip archive. This will will expand both parts automatically. On Linux I found I had to use `7zip` - the basic `unzip` tool did not work. Example:
```
sudo apt update -y && sudo apt install 7zip
7zz x VicUnlocked-Alpaca-65B.ggmlv3.q8_0.zip # Once the q8_0.bin is extracted you can delete the .zip and .z01
```

## How to run in `llama.cpp`

I use the following command line; adjust for your tastes and needs:

```
./main -t 10 -ngl 32 -m VicUnlocked-Alpaca-65B.ggmlv3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "### Instruction: Write a story about llamas\n### Response:"
```
Change `-t 10` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.

Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.

If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`

## How to run in `text-generation-webui`

Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).

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## Discord

For further support, and discussions on these models and AI in general, join us at:

[TheBloke AI's Discord server](https://discord.gg/Jq4vkcDakD)

## Thanks, and how to contribute.

Thanks to the [chirper.ai](https://chirper.ai) team!

I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.

If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.

Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.

* Patreon: https://patreon.com/TheBlokeAI
* Ko-Fi: https://ko-fi.com/TheBlokeAI

**Patreon special mentions**: Aemon Algiz, Dmitriy Samsonov, Nathan LeClaire, Trenton Dambrowitz, Mano Prime, David Flickinger, vamX, Nikolai Manek, senxiiz, Khalefa Al-Ahmad, Illia Dulskyi, Jonathan Leane, Talal Aujan, V. Lukas, Joseph William Delisle, Pyrater, Oscar Rangel, Lone Striker, Luke Pendergrass, Eugene Pentland, Sebastain Graf, Johann-Peter Hartman.

Thank you to all my generous patrons and donaters!
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Patreon special mention: Jonathan Leane; Talal Aujan. Thank you both, and to all my other patrons and donaters.

# Original model card: Aeala's VicUnlocked Alpaca 65B QLoRA


## LoRA Info:
Please note that this is a highly experimental LoRA model. It may do some good stuff, it might do some undesirable stuff. Training is paused for now. Feel free to try it!~

**Important Note**: While this is trained on a cleaned ShareGPT dataset like Vicuna used, this was trained in the *Alpaca* format, so prompting should be something like:

```
### Instruction:

<prompt> (without the <>)

### Response:
```

Current upload: checkpoint of step 1200 in training.


## Benchmarks
**wikitext2:** Coming soon...

**ptb-new:** Coming soon...

**c4-new:** Coming soon...