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

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

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"

Tessera-125B-MoE

File size: 557 Bytes

0598ff3

id,pass,tokens
lcb_hard_abc397_g,1,17629
lcb_hard_arc192_e,0,17677
lcb_hard_arc196_d,0,16399
lcb_hard_arc194_d,0,16936
lcb_hard_abc392_f,0,16895
lcb_hard_arc195_e,1,16935
lcb_hard_abc398_g,0,16691
lcb_hard_abc394_g,1,17923
lcb_medium_3805,1,16656
lcb_hard_abc394_f,1,16982
lcb_hard_arc190_c,0,17264
lcb_hard_abc387_f,0,17305
lcb_hard_arc196_b,0,17359
lcb_medium_arc192_a,1,17108
lcb_hard_arc193_b,0,20480
lcb_medium_abc399_d,1,16745
lcb_medium_abc400_d,1,16900
lcb_medium_3776,1,16989
lcb_hard_3674,0,18361
crux_o_sample_445,0,1312
crux_o_sample_136,0,3059