Instructions to use TessaCoil/K3-Stuff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use TessaCoil/K3-Stuff 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 TessaCoil/K3-Stuff:Q8_0
# Run inference directly in the terminal:
llama cli -hf TessaCoil/K3-Stuff:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf TessaCoil/K3-Stuff:Q8_0
# Run inference directly in the terminal:
llama cli -hf TessaCoil/K3-Stuff:Q8_0

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 TessaCoil/K3-Stuff:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf TessaCoil/K3-Stuff:Q8_0

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 TessaCoil/K3-Stuff:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TessaCoil/K3-Stuff:Q8_0

Use Docker

docker model run hf.co/TessaCoil/K3-Stuff:Q8_0

LM Studio
Jan
Ollama
How to use TessaCoil/K3-Stuff with Ollama:
```
ollama run hf.co/TessaCoil/K3-Stuff:Q8_0
```
Unsloth Desktop

How to use TessaCoil/K3-Stuff with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf TessaCoil/K3-Stuff:Q8_0

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": "TessaCoil/K3-Stuff:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use TessaCoil/K3-Stuff with Docker Model Runner:
```
docker model run hf.co/TessaCoil/K3-Stuff:Q8_0
```

Lemonade

How to use TessaCoil/K3-Stuff with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TessaCoil/K3-Stuff:Q8_0

Run and chat with the model

lemonade run user.K3-Stuff-Q8_0

List all available models

lemonade list

Hermes Agent

How to use TessaCoil/K3-Stuff with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf TessaCoil/K3-Stuff:Q8_0

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 TessaCoil/K3-Stuff:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TessaCoil/K3-Stuff with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf TessaCoil/K3-Stuff:Q8_0

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 "TessaCoil/K3-Stuff:Q8_0" \
  --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"

K3-Stuff

File size: 1,067 Bytes

ddf8c5b

#!/usr/bin/env bash
# k3-test/26_draft_sweep.sh — sweep DSpark --draft-max; one server per depth (flag is load-time).
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
export K3TEST_ROOT="$SCRIPT_DIR"
source "$SCRIPT_DIR/lib/common.sh"
source "$K3TEST_ROOT/lib/server.sh"
set -uo pipefail

[[ -f $K3_MODEL_PATH ]] || die "K3 missing"
CODING="$K3TEST_ROOT/prompts/coding.txt"
DRAFT="$MODEL_DIR/k3-draft/draft.gguf"
[[ -f $DRAFT ]] || die "draft missing"
THREADS="${THREADS:-56}"
BASE_SPLIT="0.3,1,1,1,1,1,1,1"
BASE=( -m "$K3_MODEL_PATH" -ngl 999 --tensor-split "$BASE_SPLIT" --cpu-moe -b 512 -ub 512 )

for MAX in 4 7 10 14; do
  if start_server "Dmax${MAX}" "${BASE[@]}" --spec-type draft-dspark -md "$DRAFT" --draft-max "$MAX" -np 1 -t "$THREADS"; then
    server_completion "k3_D_max${MAX}_cold" "$CODING" 128
    server_completion "k3_D_max${MAX}_warm" "$CODING" 128
    stop_server
  else
    echo "Dmax${MAX} failed to load" | tee "$LOG_ROOT/k3_D_max${MAX}_FAIL.txt"
  fi
done
echo "$(date +%s) 26_draft_sweep done" >> "$LOG_ROOT/k3_suite_status.txt"