Instructions to use q-future/one-align with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-future/one-align with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="q-future/one-align", trust_remote_code=True) pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("q-future/one-align", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69c30fba150b4d6096e36fccdcfdd529fe23b7d44d8f39a8b6bc14f530f45c92
- Size of remote file:
- 6.42 GB
- SHA256:
- d445a50608f025a39ac75c6da13cb9d12a4cc923f6e1b9abc4b767408eac0729
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