How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:# Run inference directly in the terminal:
llama cli -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:# Run inference directly in the terminal:
./build/bin/llama cli -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:Use Docker
docker model run hf.co/cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:Quick Links
This model is the first in a series of experiments to make my models a bit smarter. Its nowhere near done, but my initial testing was good so I'm uploading so people can check it out.
Datasets Used:
- Dolphin
- Ultrachat
- Capybara
- Augmental
- ToxicQA
- Magiccoder-Evol-Instruct-110k
- Yahoo Answers
- OpenOrca
- Airoboros 3.1
- grimulkan/physical-reasoning and theory-of-mind
Prompt Format: Chat ( The default Ooba template and Silly Tavern Template )
{System Prompt}
Username: {Input}
BotName: {Response}
Username: {Input}
BotName: {Response}
Recommended Silly Tavern Preset -> (Temp: 1.25, MinP: 0.1, RepPen: 1.03)
Recommended Kobold Horde Preset -> MinP
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF:# Run inference directly in the terminal: llama cli -hf cgato/Thespis-CurtainCall-7b-v0.2.1-GGUF: