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How to use neopolita/firefunction-v1-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="neopolita/firefunction-v1-gguf", filename="firefunction-v1_q2_k.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use neopolita/firefunction-v1-gguf with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf neopolita/firefunction-v1-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf neopolita/firefunction-v1-gguf:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf neopolita/firefunction-v1-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf neopolita/firefunction-v1-gguf:Q4_K_M
# 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 neopolita/firefunction-v1-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf neopolita/firefunction-v1-gguf:Q4_K_M
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 neopolita/firefunction-v1-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf neopolita/firefunction-v1-gguf:Q4_K_M
docker model run hf.co/neopolita/firefunction-v1-gguf:Q4_K_M
How to use neopolita/firefunction-v1-gguf with Ollama:
ollama run hf.co/neopolita/firefunction-v1-gguf:Q4_K_M
How to use neopolita/firefunction-v1-gguf with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for neopolita/firefunction-v1-gguf to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for neopolita/firefunction-v1-gguf to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for neopolita/firefunction-v1-gguf to start chatting
How to use neopolita/firefunction-v1-gguf with Docker Model Runner:
docker model run hf.co/neopolita/firefunction-v1-gguf:Q4_K_M
How to use neopolita/firefunction-v1-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull neopolita/firefunction-v1-gguf:Q4_K_M
lemonade run user.firefunction-v1-gguf-Q4_K_M
lemonade list
Terms of Use: Please check the original model
q2_k: Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.q3_k_s: Uses Q3_K for all tensorsq3_k_m: Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_Kq3_k_l: Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_Kq4_0: Original quant method, 4-bit.q4_1: Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.q4_k_s: Uses Q4_K for all tensorsq4_k_m: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_Kq5_0: Higher accuracy, higher resource usage and slower inference.q5_1: Even higher accuracy, resource usage and slower inference.q5_k_s: Uses Q5_K for all tensorsq5_k_m: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_Kq6_k: Uses Q8_K for all tensorsq8_0: Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.2-bit
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docker model run hf.co/neopolita/firefunction-v1-gguf: