Instructions to use Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix 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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix 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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix: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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix: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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
Use Docker
docker model run hf.co/Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix with Ollama:
ollama run hf.co/Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
- Unsloth Studio
How to use Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix 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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix 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 Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix to start chatting
- Docker Model Runner
How to use Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix with Docker Model Runner:
docker model run hf.co/Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
- Lemonade
How to use Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Lewdiculous/SOVL_Llama3_8B-GGUF-IQ-Imatrix:Q4_K_M
Run and chat with the model
lemonade run user.SOVL_Llama3_8B-GGUF-IQ-Imatrix-Q4_K_M
List all available models
lemonade list
- Atomic Chat
My upload speeds have been cooked and unstable lately.
Realistically I'd need to move to get a better provider.
If you want and you are able to, you can support various endeavors here (Ko-fi).
I apologize for disrupting your experience.
#llama-3 #experimental #work-in-progress
GGUF-IQ-Imatrix quants for @jeiku's ResplendentAI/SOVL_Llama3_8B.
Give them some love!
Updated! These quants have been redone with the fixes from llama.cpp/pull/6920 in mind.
Use KoboldCpp version 1.64 or higher.
Well...!
Turns out it was not just a hallucination and this model actually is pretty cool so give it a chance!
For 8GB VRAM GPUs, I recommend the Q4_K_M-imat quant for up to 12288 context sizes.
Use the provided presets.
Compatible SillyTavern presets here (simple) or here (Virt's roleplay). Use the latest version of KoboldCpp.
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