Instructions to use Motif-Technologies/Motif-3-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Motif-Technologies/Motif-3-Beta with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Motif-Technologies/Motif-3-Beta", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Motif-Technologies/Motif-3-Beta", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Motif-Technologies/Motif-3-Beta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Motif-Technologies/Motif-3-Beta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-3-Beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Motif-Technologies/Motif-3-Beta

SGLang

How to use Motif-Technologies/Motif-3-Beta with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Motif-Technologies/Motif-3-Beta" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-3-Beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Motif-Technologies/Motif-3-Beta" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Motif-Technologies/Motif-3-Beta",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Motif-Technologies/Motif-3-Beta with Docker Model Runner:
```
docker model run hf.co/Motif-Technologies/Motif-3-Beta
```

Potentially misleading information given to Artificial Analysis?

by DavCd - opened 4 days ago

Discussion

DavCd

4 days ago

•

edited 4 days ago

Shouldn't the model be at the "Open weights(Commercial Use Restricted)" criteria?
I feel like every small detail matters when you do lack PR/marketing resources.
As the model being in the 'proprietary' criteria, people would likely to show less interest.
Or is there any other reason the model being registered as a proprietary one?

dongseokmotif

Motif Technologies org 3 days ago

Thanks — that's a fair point, and you're right that these details matter, especially without a big marketing push.

You're also right on the substance: the weights are openly downloadable with no gating, so in practice this is much closer to "open weights, commercial use restricted" than fully proprietary. The commercial-use restriction on this Beta checkpoint is tied to an ongoing sovereign-AI project — a temporary constraint specific to this intermediate release, not our long-term intent for Motif-3.

We plan to lift that restriction on the final public checkpoint, so the current status reflects the Beta's situation rather than where the model is headed. We'll also look into getting the categorization corrected in the meantime. Appreciate you raising it. 🙏

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