Zero-Shot Image Classification
Transformers
Safetensors
ultravbert
feature-extraction
vela
system-one
semantic-router
image-classification
hallucination-detection
visual-grounding
encoder
preview
custom_code
Instructions to use vllm-sr/vela3-fast-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/vela3-fast-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="vllm-sr/vela3-fast-vision", trust_remote_code=True) pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/vela3-fast-vision", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/vela3-fast-vision", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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