Instructions to use thesysdev/OUI-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use thesysdev/OUI-1 with Transformers:

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

pipe = pipeline("text-generation", model="thesysdev/OUI-1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("thesysdev/OUI-1")
model = AutoModelForMultimodalLM.from_pretrained("thesysdev/OUI-1", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use thesysdev/OUI-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "thesysdev/OUI-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thesysdev/OUI-1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/thesysdev/OUI-1

SGLang

How to use thesysdev/OUI-1 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 "thesysdev/OUI-1" \
    --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": "thesysdev/OUI-1",
		"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 "thesysdev/OUI-1" \
        --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": "thesysdev/OUI-1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use thesysdev/OUI-1 with Docker Model Runner:
```
docker model run hf.co/thesysdev/OUI-1
```

andhakanoon commited on 7 days ago

Commit

68e8006

verified ·

1 Parent(s): 8cb4761

adapter card: license is Apache 2.0, same as the Gemma 4 base

Browse files

Files changed (1) hide show

adapter/README.md +2 -2

adapter/README.md CHANGED Viewed

@@ -1,7 +1,7 @@
 ---
 base_model: unsloth/diffusiongemma-26B-A4B-it
 library_name: peft
-license: gemma
 tags:
   - lora
   - diffusion-language-model
@@ -21,5 +21,5 @@ the decoder only and gives a different model; call `.merge_and_unload()` to repr
 weights, or use the merged checkpoint in the parent repo, which is what every published number
 was measured on.
-Published by Thesys under the Gemma Terms of Use; the base license and its use restrictions apply.
 See the parent repo's model card for results, serving settings and usage.

 ---
 base_model: unsloth/diffusiongemma-26B-A4B-it
 library_name: peft
+license: apache-2.0
 tags:
   - lora
   - diffusion-language-model
 weights, or use the merged checkpoint in the parent repo, which is what every published number
 was measured on.
+Published by Thesys under Apache 2.0, the same license as the base model (Gemma 4 license: https://ai.google.dev/gemma/docs/gemma_4_license).
 See the parent repo's model card for results, serving settings and usage.