# GodziLLa2 70B - GGML
- Model creator: [MayaPH](https://huggingface.co/mayaph)
- Original model: [GodziLLa2 70B](https://huggingface.co/MayaPH/GodziLLa2-70B)
## Description
This repo contains GGML format model files for [MayaPH's GodziLLa2 70B](https://huggingface.co/MayaPH/GodziLLa2-70B).
GPU acceleration is now available for Llama 2 70B GGML files, with both CUDA (NVidia) and Metal (macOS). The following clients/libraries are known to work with these files, including with GPU acceleration:
* [llama.cpp](https://github.com/ggerganov/llama.cpp), commit `e76d630` and later.
* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI.
* [KoboldCpp](https://github.com/LostRuins/koboldcpp), version 1.37 and later. A powerful GGML web UI, especially good for story telling.
* [LM Studio](https://lmstudio.ai/), a fully featured local GUI with GPU acceleration for both Windows and macOS. Use 0.1.11 or later for macOS GPU acceleration with 70B models.
* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), version 0.1.77 and later. A Python library with LangChain support, and OpenAI-compatible API server.
* [ctransformers](https://github.com/marella/ctransformers), version 0.2.15 and later. A Python library with LangChain support, and OpenAI-compatible API server.
## Repositories available
* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/GodziLLa2-70B-GPTQ)
* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/GodziLLa2-70B-GGML)
* [MayaPH's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/MayaPH/GodziLLa2-70B)
## Prompt template: Alpaca
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
```
## Compatibility
### Requires llama.cpp [commit `e76d630`](https://github.com/ggerganov/llama.cpp/commit/e76d630df17e235e6b9ef416c45996765d2e36fb) or later.
Or one of the other tools and libraries listed above.
To use in llama.cpp, you must add `-gqa 8` argument.
For other UIs and libraries, please check the docs.
## Explanation of the new k-quant methods
