Image-Text-to-Text
Transformers
Safetensors
English
opencua
feature-extraction
VLM
Computer-Use-Agent
OS-Agent
GUI
Grounding
conversational
custom_code
4-bit precision
bitsandbytes
Instructions to use sujitvasanth/OpenCUA7BQfp164bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sujitvasanth/OpenCUA7BQfp164bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="sujitvasanth/OpenCUA7BQfp164bit", trust_remote_code=True) 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sujitvasanth/OpenCUA7BQfp164bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use sujitvasanth/OpenCUA7BQfp164bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sujitvasanth/OpenCUA7BQfp164bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sujitvasanth/OpenCUA7BQfp164bit", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/sujitvasanth/OpenCUA7BQfp164bit
- SGLang
How to use sujitvasanth/OpenCUA7BQfp164bit 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 "sujitvasanth/OpenCUA7BQfp164bit" \ --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": "sujitvasanth/OpenCUA7BQfp164bit", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "sujitvasanth/OpenCUA7BQfp164bit" \ --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": "sujitvasanth/OpenCUA7BQfp164bit", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use sujitvasanth/OpenCUA7BQfp164bit with Docker Model Runner:
docker model run hf.co/sujitvasanth/OpenCUA7BQfp164bit
Commit History
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Verified signature2 small changesa to work with newer transformers libraries (old value is commented out) @property def _supports_sdpa(self): return True #self.language_model._supports_sdpa ---- if past_key_values is not None: if isinstance(past_key_values, Cache): cache_length = past_key_values.get_seq_length() past_length = cache_length # past_key_values.seen_tokens --------a7e4cd2 -
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Verified signature--- base_model: - Qwen/Qwen2.5-VL-7B-Instruct datasets: - xlangai/AgentNet - xlangai/aguvis-stage1 - smolagents/aguvis-stage-2 - osunlp/UGround-V1-Data language: - en license: mit metrics: - accuracy - code_eval pipeline_tag: image-text-to-text library_name: transformers tags: - VLM - Computer-Use-Agent - OS-Agent - GUI - Grounding --- <h1 style=" font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Helvetica,Arial,sans-serif; font-size:48px; font-weight:700; line-height:1.25; text-align:center; margin:0 0 24px;"> OpenCUA: Open Foundations for Computer-Use Agents </h1> <div style=" display:flex; justify-content:center; gap:12px; flex-wrap:wrap; margin-bottom:28px;"> <a href="https://opencua.xlang.ai/" style=" display:inline-block; padding:8px 24px; background:#2b2b2b; color:#ffffff; border-radius:36px; text-decoration:none; font-weight:600; font-size:16px;"> 🌐 Website </a> <a href="https://arxiv.org/abs…2db370b -
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