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Nitral-AI/Nyan-Stunna-7B
Nitral-AI/Kunocchini-7b-128k-test
Q2_K
Q3_K_L
Q3_K_M
Q3_K_S
Q4_0
Q4_1
Q4_K_S
Q4_k_m
Q5_0
Q5_1
Q6_K
Q5_K_S
Q5_k_m
Q8_0
128k
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Instructions to use AlekseiPravdin/NSK-128k-7B-slerp-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 AlekseiPravdin/NSK-128k-7B-slerp-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 AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
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 AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
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 AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
Use Docker
docker model run hf.co/AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use AlekseiPravdin/NSK-128k-7B-slerp-gguf with Ollama:
ollama run hf.co/AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
- Unsloth Studio
How to use AlekseiPravdin/NSK-128k-7B-slerp-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 AlekseiPravdin/NSK-128k-7B-slerp-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 AlekseiPravdin/NSK-128k-7B-slerp-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AlekseiPravdin/NSK-128k-7B-slerp-gguf to start chatting
- Atomic Chat new
- Docker Model Runner
How to use AlekseiPravdin/NSK-128k-7B-slerp-gguf with Docker Model Runner:
docker model run hf.co/AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
- Lemonade
How to use AlekseiPravdin/NSK-128k-7B-slerp-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AlekseiPravdin/NSK-128k-7B-slerp-gguf:Q4_K_M
Run and chat with the model
lemonade run user.NSK-128k-7B-slerp-gguf-Q4_K_M
List all available models
lemonade list
- Xet hash:
- 70341b15eda34bb60316ffcc698a50030041ad3e0f06f4c2abad76300e771cb9
- Size of remote file:
- 4.14 GB
- SHA256:
- 147dfff6010a30d83e6f6579386f335e3dfd709d2b8fff59503dc92edb94dcee
·
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