Create README.md

README.md

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+---
+inference: false
+---
+
+# Ejafa's Vicuna Vanilla 1.1 7B GGML
+
+
+These files are GGML format model files for [Ejafa's Vicuna Vanilla 1.1 7B](https://huggingface.co/Ejafa/vicuna_7B_vanilla_1.1).
+
+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 8 -ngl 32 -m vicuna_7B_vanilla_1.1.ggmlv3.q5_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "prompt goes here"
+```
+Change `-t 8` 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`
+
+## 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 the [TheBloke](https://huggingface.co/TheBloke) for inspiring and providing almost all of the readme here!
+
+Thanks to the [Ejafa](https://huggingface.co/Ejafa) for providing checkpoints of the model.
+
+Thanks to the [Georgi Gerganov](https://github.com/ggerganov) and all of the awesome people in the AI community.
+