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A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
USER: Hello!
ASSISTANT: Hello!</s>
USER: How are you?
ASSISTANT: I am good.</s>q4_0 + q5_1q4_0 and q5_1 version for my own use. Please let me know if there is demand for other quantizations.
These should be compatbile with any UIs, tools and libraries released since late May.| Name | Quant method | Bits | Size | Max RAM required | Use case |
|---|---|---|---|---|---|
| vicuna-13b-v1.3-ger.ggmlv3.q4_0.bin | q4_0 | 4 | 7.37 GB | ~9.8 GB | Original llama.cpp quant method, 4-bit. |
| vicuna-13b-v1.3-ger.ggmlv3.q5_1.bin | q5_1 | 5 | 9.78 GB | ~12.3 GB | Original quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
llama.cpp./main -t 10 -ngl 32 -m vicuna-13b-v1.3-ger.ggmlv3.q4_0.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "You are an story writing assistant who writes very long, detailed and interesting stories\n\nUser:\nWrite a story about llamas\nAssistant:\n"-t 1 to get best performance.-t 10 to the number of physical CPU cores you have, or a lower number depending on what gives best performance.-ngl 32 to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.-p <PROMPT> argument with -i -instext-generation-webui