Instructions to use tensorblock/NeuralSynthesis-7B-v0.3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/NeuralSynthesis-7B-v0.3-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
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 tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
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 tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/NeuralSynthesis-7B-v0.3-GGUF with Ollama:
ollama run hf.co/tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/NeuralSynthesis-7B-v0.3-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
- Lemonade
How to use tensorblock/NeuralSynthesis-7B-v0.3-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/NeuralSynthesis-7B-v0.3-GGUF:Q2_K
Run and chat with the model
lemonade run user.NeuralSynthesis-7B-v0.3-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Download NeuralSynthesis-7B-v0.3-Q2_K.gguf from tensorblock/NeuralSynthesis-7B-v0.3-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 2.72 GB
-
https://huggingface.co/tensorblock/NeuralSynthesis-7B-v0.3-GGUF/resolve/e52cb193b2db050e1f23ce09de74244e5b82b703/NeuralSynthesis-7B-v0.3-Q2_K.gguf
- Command line
-
hf download hf://tensorblock/NeuralSynthesis-7B-v0.3-GGUF@e52cb193b2db050e1f23ce09de74244e5b82b703/NeuralSynthesis-7B-v0.3-Q2_K.gguf
-
curl -L -o NeuralSynthesis-7B-v0.3-Q2_K.gguf https://huggingface.co/tensorblock/NeuralSynthesis-7B-v0.3-GGUF/resolve/e52cb193b2db050e1f23ce09de74244e5b82b703/NeuralSynthesis-7B-v0.3-Q2_K.gguf
2.72 GB
- Xet hash:
- 3240f7430a2f922ba57b6c048d1cdf8c4aeb63edd6b3fe8100251b4bded86a44
- Size of remote file:
- 2.72 GB
- SHA256:
- b250b1b1ed1ebe954b4333055bc0a8c57d6e536ada10cd24901f4fe26d4bd0ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.