How to use ThorBaller/yes with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ThorBaller/yes")
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ThorBaller/yes", device_map="auto")
How to use ThorBaller/yes with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ThorBaller/yes:Q8_0 # Run inference directly in the terminal: llama cli -hf ThorBaller/yes:Q8_0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ThorBaller/yes:Q8_0 # Run inference directly in the terminal: llama cli -hf ThorBaller/yes:Q8_0
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf ThorBaller/yes:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ThorBaller/yes:Q8_0
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf ThorBaller/yes:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ThorBaller/yes:Q8_0
docker model run hf.co/ThorBaller/yes:Q8_0
How to use ThorBaller/yes with Ollama:
ollama run hf.co/ThorBaller/yes:Q8_0
How to use ThorBaller/yes with Docker Model Runner:
How to use ThorBaller/yes with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ThorBaller/yes:Q8_0
lemonade run user.yes-Q8_0
lemonade list
A llama3 model im gguf form that was finetuned on a pubmed dataset.
8-bit
