Instructions to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M

Ollama
How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with Ollama:
```
ollama run hf.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
```

Unsloth Studio

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF to start chatting

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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": "iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 "iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with Docker Model Runner:
```
docker model run hf.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
```

Lemonade

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-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 iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

kobkrit commited on 15 days ago

Commit

b2607f0

verified ·

1 Parent(s): 2184955

Add model card

Browse files

Files changed (1) hide show

README.md +86 -0

README.md ADDED Viewed

	@@ -0,0 +1,86 @@

+---
+license: other
+license_name: nvidia-open-model-agreement
+license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/
+language:
+- th
+- en
+base_model: iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b
+pipeline_tag: text-generation
+library_name: gguf
+tags:
+- thai
+- legal
+- openthai
+- gguf
+- llama.cpp
+- mixture-of-experts
+---
+<div align="center">
+<img src="https://huggingface.co/spaces/openthaigpt/README/resolve/main/openthai-logo-white.png" width="160" alt="OpenThai">
+# OpenThai 2.0 Legal 30B-A3B — GGUF
+**Official** GGUF quantizations of [iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b](https://huggingface.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b)
+[Website](https://openthai.aieat.or.th) · [Announcement](https://openthai.aieat.or.th/openthai2p0-legal) · [Live demo](https://iapp.co.th/openmodels/openthai2p0-legal) · [Discord](https://discord.gg/7KDdKkBGUs)
+</div>
+An open-weight Thai legal LLM that recalls Thai statutes and cites the exact law name and
+section (มาตรา) as structured JSON. 30B Mixture-of-Experts with only ~3B parameters active
+per token — which is why a 30B model runs comfortably on modest hardware.
+**Use it with retrieval.** Open-book citation accuracy is 0.99 versus 0.07–0.40 from pure
+memory. Pair it with [OpenThaiRAG](https://github.com/OpenThaiGPT/openthairag) or your own
+retrieval over authoritative statute text.
+## Quants
+| File | Quant | Size | Notes |
+|---|---|---|---|
+| `openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b.Q4_K_M.gguf` | Q4_K_M | ~18 GB | **Recommended.** Fits a 24 GB GPU. |
+| `openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b.Q5_K_M.gguf` | Q5_K_M | ~21 GB | Higher quality. |
+| `openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b.Q8_0.gguf` | Q8_0 | ~32 GB | Near-lossless. |
+## Usage
+**Ollama**
+```bash
+ollama run hf.co/iapp/openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b-GGUF:Q4_K_M
+```
+**llama.cpp**
+```bash
+llama-cli -m openthai2.0-legal-thaillm-nemotron-3-nano-30b-a3b.Q4_K_M.gguf \
+  -p "ลักทรัพย์ในเวลากลางคืน ผิดมาตราใด" -n 1024 --temp 0.3
+```
+The chat template is embedded in the GGUF. Recommended sampling: `temperature=0.3`,
+`top_p=0.9`. Architecture is a hybrid Mamba2-Transformer MoE (NVIDIA
+Nemotron-3-Nano-30B-A3B base) — use a recent llama.cpp build.
+## ⚠️ Responsible use
+Outputs are **decision support, not legal advice**. Verify every citation against the
+current statute text. Near-miss rejection — telling the governing section from a closely
+related one — is the hardest task for every model tested, this one included.
+## Citation
+```bibtex
+@misc{openthai2026legal,
+  title  = {OpenThai 2.0 Legal: An Open-Weight Thai Legal Language Model},
+  author = {Viriyayudhakorn, Kobkrit and Yuenyong, Sumeth and Chay-intr, Thodsaporn},
+  year   = {2026},
+  url    = {https://openthai.aieat.or.th/openthai2p0-legal}
+}
+```
+---
+*OpenThai (formerly OpenThaiGPT) — free, open-weight Thai large language models from AIEAT
+and iApp Technology, built here on the NVIDIA Nemotron and NeMo stack. With thanks to the
+community members who published unofficial GGUF conversions before these existed.*