Instructions to use AIIT-Threshold/Tessera-1B 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 AIIT-Threshold/Tessera-1B 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 AIIT-Threshold/Tessera-1B:Q6_K # Run inference directly in the terminal: llama cli -hf AIIT-Threshold/Tessera-1B:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AIIT-Threshold/Tessera-1B:Q6_K # Run inference directly in the terminal: llama cli -hf AIIT-Threshold/Tessera-1B:Q6_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 AIIT-Threshold/Tessera-1B:Q6_K # Run inference directly in the terminal: ./build/bin/llama cli -hf AIIT-Threshold/Tessera-1B:Q6_K
Use Docker
docker model run hf.co/AIIT-Threshold/Tessera-1B:Q6_K
- Llama new
- LM Studio
- Jan
- Ollama
How to use AIIT-Threshold/Tessera-1B with Ollama:
ollama run hf.co/AIIT-Threshold/Tessera-1B:Q6_K
- Unsloth Desktop
- Docker Model Runner
How to use AIIT-Threshold/Tessera-1B with Docker Model Runner:
docker model run hf.co/AIIT-Threshold/Tessera-1B:Q6_K
- Lemonade
How to use AIIT-Threshold/Tessera-1B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AIIT-Threshold/Tessera-1B:Q6_K
Run and chat with the model
lemonade run user.Tessera-1B-Q6_K
List all available models
lemonade list
- Atomic Chat
Ctrl+K
Add WADT dilemma fine-tune adapter โ proof-of-concept SFT run, live on the shared 3090 under VRAM guard
e3aa5ce verified