Instructions to use netcat420/MFANNv0.11-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use netcat420/MFANNv0.11-GGUF with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("netcat420/MFANNv0.11-GGUF", set_active=True) - llama-cpp-python
How to use netcat420/MFANNv0.11-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="netcat420/MFANNv0.11-GGUF", filename="MFANNv0.11.gguf", )
llm.create_chat_completion( messages = "\"I like you. I love you\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use netcat420/MFANNv0.11-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf netcat420/MFANNv0.11-GGUF # Run inference directly in the terminal: llama-cli -hf netcat420/MFANNv0.11-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf netcat420/MFANNv0.11-GGUF # Run inference directly in the terminal: llama-cli -hf netcat420/MFANNv0.11-GGUF
Use pre-built binary
# 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 netcat420/MFANNv0.11-GGUF # Run inference directly in the terminal: ./llama-cli -hf netcat420/MFANNv0.11-GGUF
Build from source code
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 netcat420/MFANNv0.11-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf netcat420/MFANNv0.11-GGUF
Use Docker
docker model run hf.co/netcat420/MFANNv0.11-GGUF
- LM Studio
- Jan
- Ollama
How to use netcat420/MFANNv0.11-GGUF with Ollama:
ollama run hf.co/netcat420/MFANNv0.11-GGUF
- Unsloth Studio new
How to use netcat420/MFANNv0.11-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 netcat420/MFANNv0.11-GGUF to start chatting
Install Unsloth Studio (Windows)
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 netcat420/MFANNv0.11-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for netcat420/MFANNv0.11-GGUF to start chatting
- Docker Model Runner
How to use netcat420/MFANNv0.11-GGUF with Docker Model Runner:
docker model run hf.co/netcat420/MFANNv0.11-GGUF
- Lemonade
How to use netcat420/MFANNv0.11-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull netcat420/MFANNv0.11-GGUF
Run and chat with the model
lemonade run user.MFANNv0.11-GGUF-{{QUANT_TAG}}List all available models
lemonade list
MFANN 8b version 0.11 4-bit GGUF (Q4_K_S).
fine-tuned on the MFANN dataset as of 5/22/24 as it is an ever expanding dataset. these are the GGUF quantized weights quantized to Q4_K_S and requires a llama.cpp application to run.
SYSTEM PROMPT:
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a helpful, respectful and honest assistant. Always answer as helpfully as possible. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. <|eot_id|>
- Downloads last month
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We're not able to determine the quantization variants.
