Text Generation
Transformers
Safetensors
English
diffusion_gemma
image-text-to-text
diffusion-language-model
generative-ui
openui
openui-lang
gemma
conversational
Instructions to use thesysdev/OUI-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
| base_model: unsloth/diffusiongemma-26B-A4B-it | |
| library_name: peft | |
| license: apache-2.0 | |
| tags: | |
| - lora | |
| - diffusion-language-model | |
| - generative-ui | |
| - openui-lang | |
| # OUI-1 LoRA adapter | |
| The PEFT adapter that produced the merged weights in the parent repo, `thesysdev/OUI-1`. | |
| Rank 64, alpha 128, 205 target modules (the decoder's q, k, v, o, gate, up and down projections), | |
| trained on `unsloth/diffusiongemma-26B-A4B-it`, a mirror of `google/diffusiongemma-26B-A4B-it`. | |
| It is a tied LoRA: DiffusionGemma's encoder and decoder share weight storage, so merging the | |
| decoder deltas adapts both passes. `PeftModel.from_pretrained(base, adapter)` on its own wraps | |
| the decoder only and gives a different model; call `.merge_and_unload()` to reproduce the merged | |
| 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. | |