Instructions to use steef68/ATLAS-QUANTUM 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 steef68/ATLAS-QUANTUM 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 steef68/ATLAS-QUANTUM:Q2_K # Run inference directly in the terminal: llama cli -hf steef68/ATLAS-QUANTUM:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf steef68/ATLAS-QUANTUM:Q2_K # Run inference directly in the terminal: llama cli -hf steef68/ATLAS-QUANTUM:Q2_K
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf steef68/ATLAS-QUANTUM:Q2_K # Run inference directly in the terminal: ./build/bin/llama cli -hf steef68/ATLAS-QUANTUM:Q2_K
Use Docker
docker model run hf.co/steef68/ATLAS-QUANTUM:Q2_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use steef68/ATLAS-QUANTUM with Ollama:
ollama run hf.co/steef68/ATLAS-QUANTUM:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use steef68/ATLAS-QUANTUM with Docker Model Runner:
docker model run hf.co/steef68/ATLAS-QUANTUM:Q2_K
- Lemonade
How to use steef68/ATLAS-QUANTUM with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull steef68/ATLAS-QUANTUM:Q2_K
Run and chat with the model
lemonade run user.ATLAS-QUANTUM-Q2_K
List all available models
lemonade list
- Atomic Chat
Update README.md
#3
by derricka59 - opened
Explanation of Additions:
- Metadata Block: Includes essential details such as
library_name,tags,datasets,model_architecture, and other relevant fields to align with Hugging Face's model card standards. - Model Details: Expands on model usage, applications, and limitations.
- Resources and Licensing: Provides clear references for further support and licensing information.
- Placeholders: Marked where dataset details are missing for future updates.