Instructions to use datlaaaaaaa/01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use datlaaaaaaa/01 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 datlaaaaaaa/01
# Run inference directly in the terminal:
llama cli -hf datlaaaaaaa/01

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf datlaaaaaaa/01
# Run inference directly in the terminal:
llama cli -hf datlaaaaaaa/01

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 datlaaaaaaa/01
# Run inference directly in the terminal:
./llama-cli -hf datlaaaaaaa/01

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 datlaaaaaaa/01
# Run inference directly in the terminal:
./build/bin/llama-cli -hf datlaaaaaaa/01

Use Docker

docker model run hf.co/datlaaaaaaa/01

LM Studio
Jan
Ollama
How to use datlaaaaaaa/01 with Ollama:
```
ollama run hf.co/datlaaaaaaa/01
```
Unsloth Desktop

How to use datlaaaaaaa/01 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datlaaaaaaa/01

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": "datlaaaaaaa/01"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use datlaaaaaaa/01 with Docker Model Runner:
```
docker model run hf.co/datlaaaaaaa/01
```

Lemonade

How to use datlaaaaaaa/01 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull datlaaaaaaa/01

Run and chat with the model

lemonade run user.01-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use datlaaaaaaa/01 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datlaaaaaaa/01

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 datlaaaaaaa/01

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use datlaaaaaaa/01 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf datlaaaaaaa/01

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 "datlaaaaaaa/01" \
  --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"

File size: 877 Bytes

f205c04

{"artifact_digest":"sha256:1aba551e6153d713d64c87c8a23592b492060a3812c7de69c0087b26648691f8","declared":{"p95_latency_ms":3456,"peak_rss_bytes":946022809,"size_bytes":703391427},"files":[{"digest":"sha256:0c57fbef9c9bdd808d0a942be862341efddf3a1e68ce30a8c749fbc41ece263c","path":"model.gguf","size_bytes":639446752}],"hardware_class":"mt-3g","hotkey":"5HBZ1AWfxDcuM2o9yUPybzRWgynXKfM9KqRG9Xe7bQAFCs2c","load":{"base_model":"Qwen/Qwen3-0.6B@c1899de289a04d12100db370d81485cdf75e47ca","entrypoint":"model.gguf","format":"gguf","max_input":{"tokens":512},"preprocessing":{"tokenizer":"tokenizer.json"},"quantization":""},"round_index":1237,"sealed":null,"signature":"021ed43f3733cd1331916ebb5bb92dbb9074a844eb5bf9cdd8750e97fcc12f734d0150dd95ff35e48615a5beeb7d72c0ae0b378175dda54d52ec77bc59cc528d","source":"hf:datlaaaaaaa/01@c0de1237","system":null,"track":"code","version":"0.1.2"}