Instructions to use Lewdiculous/Aurora_l3_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/Aurora_l3_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/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/Aurora_l3_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/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: llama cli -hf Lewdiculous/Aurora_l3_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/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Lewdiculous/Aurora_l3_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/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M
Use Docker
docker model run hf.co/Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix with Ollama:
ollama run hf.co/Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M
- Unsloth Studio
How to use Lewdiculous/Aurora_l3_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/Aurora_l3_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/Aurora_l3_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/Aurora_l3_8B-GGUF-IQ-Imatrix to start chatting
- Docker Model Runner
How to use Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix with Docker Model Runner:
docker model run hf.co/Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M
- Lemonade
How to use Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Lewdiculous/Aurora_l3_8B-GGUF-IQ-Imatrix:Q4_K_M
Run and chat with the model
lemonade run user.Aurora_l3_8B-GGUF-IQ-Imatrix-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Outdated:
Outdaded tokenizer configuration!
This is only kept for historical purposes, use the newer models instead of this one. Busy times, for the faint of heart, wait the storm.
This is yet another attempt with hopefully more stable formatting for quotes/asterisks dialogues.
GGUF-IQ-Imatrix quants for ResplendentAI/Aurora_l3_8B.
Recommended presets here or here.
Use the latest version of KoboldCpp. Use the provided presets.
This is all still highly experimental, modified configs were used to avoid the tokenizer issues, let the authors know how it performs for you, feedback is more important than ever now.
Original model information:
Aurora
A more poetic offering with a focus on perfecting the quote/asterisk RP format. I have strengthened the creative writing training.
Make sure your example messages and introduction are formatted cirrectly. You must respond in quotes if you want the bot to follow. Thoroughly tested and did not see a single issue. The model can still do plaintext/aserisks if you choose.
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