Instructions to use Voidstackloop/Tessera-125B-MoE 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 Voidstackloop/Tessera-125B-MoE 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 Voidstackloop/Tessera-125B-MoE:IQ2_S # Run inference directly in the terminal: llama cli -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Voidstackloop/Tessera-125B-MoE:IQ2_S # Run inference directly in the terminal: llama cli -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
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 Voidstackloop/Tessera-125B-MoE:IQ2_S # Run inference directly in the terminal: ./llama-cli -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
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 Voidstackloop/Tessera-125B-MoE:IQ2_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
Use Docker
docker model run hf.co/Voidstackloop/Tessera-125B-MoE:IQ2_S
- Llama new
- LM Studio
- Jan
- Ollama
How to use Voidstackloop/Tessera-125B-MoE with Ollama:
ollama run hf.co/Voidstackloop/Tessera-125B-MoE:IQ2_S
- Unsloth Desktop
- Pi
How to use Voidstackloop/Tessera-125B-MoE with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Voidstackloop/Tessera-125B-MoE:IQ2_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Voidstackloop/Tessera-125B-MoE with Docker Model Runner:
docker model run hf.co/Voidstackloop/Tessera-125B-MoE:IQ2_S
- Lemonade
How to use Voidstackloop/Tessera-125B-MoE with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Voidstackloop/Tessera-125B-MoE:IQ2_S
Run and chat with the model
lemonade run user.Tessera-125B-MoE-IQ2_S
List all available models
lemonade list
- Hermes Agent
How to use Voidstackloop/Tessera-125B-MoE with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Voidstackloop/Tessera-125B-MoE:IQ2_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Voidstackloop/Tessera-125B-MoE with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Voidstackloop/Tessera-125B-MoE:IQ2_S
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Voidstackloop/Tessera-125B-MoE:IQ2_S" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download benchmarks/results/k448_code_think16k_full_compact.csv from Voidstackloop/Tessera-125B-MoE: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/Voidstackloop/Tessera-125B-MoE/resolve/main/benchmarks/results/k448_code_think16k_full_compact.csv
- Command line
-
hf download hf://Voidstackloop/Tessera-125B-MoE/benchmarks/results/k448_code_think16k_full_compact.csv
-
curl -L -o k448_code_think16k_full_compact.csv https://huggingface.co/Voidstackloop/Tessera-125B-MoE/resolve/main/benchmarks/results/k448_code_think16k_full_compact.csv
2.93 kB
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| lcb_hard_3674,0,17132 | |
| crux_o_sample_595,1,564 | |
| crux_i_sample_123,1,2206 | |
| crux_o_sample_32,1,402 | |
| crux_i_sample_198,1,982 | |
| crux_o_sample_630,1,1180 | |
| crux_i_sample_423,1,4725 | |
| crux_o_sample_388,1,428 | |
| crux_i_sample_379,1,467 | |
| crux_o_sample_64,1,838 | |
| crux_i_sample_506,1,542 | |
| crux_o_sample_560,1,425 | |
| crux_i_sample_204,1,541 | |
| crux_o_sample_760,1,319 | |
| crux_i_sample_308,1,753 | |
| crux_o_sample_379,1,421 | |
| crux_i_sample_223,1,386 | |
| crux_o_sample_184,1,322 | |
| crux_i_sample_374,1,654 | |
| crux_o_sample_385,1,726 | |
| crux_i_sample_11,1,404 | |
| crux_o_sample_155,1,1422 | |
| crux_i_sample_39,1,346 | |
| crux_o_sample_387,1,195 | |
| crux_i_sample_544,1,2334 | |
| crux_o_sample_445,0,1312 | |
| crux_i_sample_257,1,999 | |
| crux_o_sample_144,1,164 | |
| crux_i_sample_610,1,2645 | |
| crux_o_sample_728,1,274 | |
| crux_i_sample_490,1,513 | |
| crux_o_sample_670,1,694 | |
| crux_i_sample_20,1,295 | |
| crux_o_sample_694,1,623 | |
| crux_i_sample_551,1,940 | |
| crux_o_sample_747,1,394 | |
| crux_i_sample_260,1,698 | |
| crux_o_sample_286,1,795 | |
| crux_i_sample_549,1,468 | |
| crux_o_sample_650,1,230 | |
| crux_i_sample_783,1,673 | |
| crux_o_sample_114,1,536 | |
| crux_i_sample_457,1,790 | |
| crux_o_sample_611,1,287 | |
| crux_i_sample_515,1,326 | |
| crux_o_sample_405,1,355 | |
| crux_i_sample_336,1,1078 | |
| crux_o_sample_349,1,867 | |
| crux_i_sample_663,1,302 | |
| crux_o_sample_599,1,999 | |
| crux_i_sample_149,1,1678 | |
| crux_o_sample_669,1,647 | |
| crux_i_sample_703,1,787 | |
| crux_o_sample_136,0,2757 | |
| crux_i_sample_608,1,633 | |
| crux_o_sample_210,1,379 | |
| crux_i_sample_673,1,792 | |
| crux_o_sample_682,1,505 | |
| crux_i_sample_291,1,1122 | |
| crux_o_sample_561,1,282 | |
| crux_i_sample_557,1,983 | |