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---
inference: false
language:
- en
tags:
- llama
- text-generation-inference
---
# lmsys's Longchat-7B-v1.5-32k GGML
These files are GGML format model files for [lmsys's Longchat-7B-v1.5-32k](https://huggingface.co/lmsys/longchat-7b-v1.5-32k).
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)
## How to run in `llama.cpp`
I use the following command line, adjust for your tastes and needs:
```
./main -t 2 -ngl 32 -m longchat-7b-v1.5-32k.ggmlv3.q4_0.bin --color --rope-freq-scale 0.25 --rope-freq-base 240000 -c 32768 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "prompt goes here"
```
Change `-t 2` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.
Change `-ngl 26` 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`, you can use `--interactive-first` to start in interactive mode.
## Compatibility
I have uploded bothe the original llama.cpp quant methods (`q4_0, q4_1, q5_0, q5_1, q8_0`) as well as the new k-quant methods (`q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K`).
Please refer to [llama.cpp](https://github.com/ggerganov/llama.cpp) and [TheBloke](https://huggingface.co/TheBloke)'s GGML models for further explanation.
## 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).
<!-- footer start -->
## Thanks
Thanks to [TheBloke](https://huggingface.co/TheBloke) for inspiration and providing almost all of the readme here!
Thanks to [lmsys](https://huggingface.co/lmsys) for providing checkpoints of the model.
Thanks to [Georgi Gerganov](https://github.com/ggerganov) and all of the awesome people in the AI community. |