Instructions to use arcee-ai/Trinity-Nano-Preview-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use arcee-ai/Trinity-Nano-Preview-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("arcee-ai/Trinity-Nano-Preview-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use arcee-ai/Trinity-Nano-Preview-GGUF 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 arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

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 arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

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 arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

Use Docker

docker model run hf.co/arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use arcee-ai/Trinity-Nano-Preview-GGUF with Ollama:
```
ollama run hf.co/arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
```

Unsloth Studio

How to use arcee-ai/Trinity-Nano-Preview-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for arcee-ai/Trinity-Nano-Preview-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for arcee-ai/Trinity-Nano-Preview-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for arcee-ai/Trinity-Nano-Preview-GGUF to start chatting

How to use arcee-ai/Trinity-Nano-Preview-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use arcee-ai/Trinity-Nano-Preview-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

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 "arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M" \
  --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"

Docker Model Runner
How to use arcee-ai/Trinity-Nano-Preview-GGUF with Docker Model Runner:
```
docker model run hf.co/arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M
```

Lemonade

How to use arcee-ai/Trinity-Nano-Preview-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Trinity-Nano-Preview-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use arcee-ai/Trinity-Nano-Preview-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

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 arcee-ai/Trinity-Nano-Preview-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

bartowski commited on Dec 1, 2025

Commit

9428169

verified ·

1 Parent(s): 6e7dada

Create README.md

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+---
+license: apache-2.0
+language:
+- en
+- es
+- fr
+- de
+- it
+- pt
+- ru
+- ar
+- hi
+- ko
+- zh
+library_name: transformers
+base_model:
+- arcee-ai/Trinity-Nano-Preview
+base_model_relation: quantized
+---
+<div align="center">
+  <picture>
+    <img
+      src="https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/i-v1KyAMOW_mgVGeic9WJ.png"
+      alt="Arcee Trinity Mini"
+      style="max-width: 100%; height: auto;"
+    >
+  </picture>
+</div>
+# Trinity Nano Preview GGUF
+Trinity Nano Preview is a preview of Arcee AI's 6B MoE model with 1B active parameters. It is the small-sized model in our new Trinity family, a series of open-weight models for enterprise and tinkerers alike.
+This is a chat tuned model, with a delightful personality and charm we think users will love. We note that this model is pushing the limits of sparsity in small language models with only 800M non-embedding parameters active per token, and as such **may be unstable** in certain use cases, especially in this preview.
+This is an *experimental* release, it's fun to talk to but will not be hosted anywhere, so download it and try it out yourself!
+These are the GGUF files for running on llama.cpp powered platforms
+***
+Trinity Nano Preview is trained on 10T tokens gathered and curated through a key partnership with [Datology](https://www.datologyai.com/), building upon the excellent dataset we used on [AFM-4.5B](https://huggingface.co/arcee-ai/AFM-4.5B) with additional math and code.
+Training was performed on a cluster of 512 H200 GPUs powered by [Prime Intellect](https://www.primeintellect.ai/) using HSDP parallelism.
+More details, including key architecture decisions, can be found on our blog [here](https://www.arcee.ai/blog)
+***
+## Model Details
+* **Model Architecture:** AfmoeForCausalLM
+* **Parameters:** 6B, 1B active
+* **Experts:** 128 total, 8 active, 1 shared
+* **Context length:** 128k
+* **Training Tokens:** 10T
+* **License:** [Apache 2.0](https://huggingface.co/arcee-ai/Trinity-Mini#license)
+***
+<div align="center">
+  <picture>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/sSVjGNHfrJKmQ6w8I18ek.png" style="background-color:ghostwhite;padding:5px;" width="17%" alt="Powered by Datology">
+  </picture>
+</div>
+### Running our model
+- [llama.cpp](https://huggingface.co/arcee-ai/Trinity-Mini#llamacpp)
+- [LM Studio](https://huggingface.co/arcee-ai/Trinity-Mini#lm-studio)
+## llama.cpp
+Supported in llama.cpp release b7061
+Download the latest [llama.cpp release](https://github.com/ggml-org/llama.cpp/releases)
+```
+llama-server -hf arcee-ai/Trinity-Nano-Preview-GGUF:q4_k_m
+```
+## LM Studio
+Supported in latest LM Studio runtime
+Update to latest available, then verify your runtime by:
+1. Click "Power User" at the bottom left
+2. Click the green "Developer" icon at the top left
+3. Select "LM Runtimes" at the top
+4. Refresh the list of runtimes and verify that the latest is installed
+Then, go to Model Search and search for `arcee-ai/Trinity-Nano-Preview-GGUF`, download your prefered size, and load it up in the chat
+## License
+Trinity-Nano-Preview is released under the Apache-2.0 license.