# gpt4-x-vicuna-13B-GGML
These files are GGML format model files of [NousResearch's gpt4-x-vicuna-13b](https://huggingface.co/NousResearch/gpt4-x-vicuna-13b).
GGML files are for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp).
## Repositories available
* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GPTQ).
* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GGML).
* [float16 HF model for unquantised and 8bit GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-HF).
## 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.
For files compatible with the previous version of llama.cpp, please see branch `previous_llama_ggmlv2`.
## Provided files
| Name | Quant method | Bits | Size | RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
`gpt4-x-vicuna-13B.ggmlv3.q4_0.bin` | q4_0 | 4bit | 8.14GB | 10GB | 4-bit. |
`gpt4-x-vicuna-13B.ggmlv3.q4_1.bin` | q4_1 | 4bit | 8.95GB | 10GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.|
`gpt4-x-vicuna-13B.ggmlv3.q5_0.bin` | q5_0 | 5bit | 8.95GB | 11GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
`gpt4-x-vicuna-13B.ggmlv3.q5_1.bin` | q5_1 | 5bit | 9.76GB | 12GB | 5-bit. Even higher accuracy, higher resource usage and slower inference. |
`gpt4-x-vicuna-13B.ggmlv3.q8_0.bin` | q8_0 | 8bit | 16GB | 18GB | 8-bit. Almost indistinguishable from float16. Huge resource use and slow. Not recommended for normal use.|
## How to run in `llama.cpp`
I use the following command line; adjust for your tastes and needs:
```
./main -t 12 -m gpt4-x-vicuna-13B.ggmlv3.q4_2.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Write a story about llamas
### Response:"
```
Change `-t 12` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.
If you want to have a chat-style conversation, replace the `-p 