Zero-Shot Image Classification
Transformers
Safetensors
tipsv2
feature-extraction
vision
image-text
contrastive-learning
zero-shot
custom_code
Instructions to use google/tipsv1-s14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tipsv1-s14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/tipsv1-s14", 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("google/tipsv1-s14", trust_remote_code=True) model = AutoModel.from_pretrained("google/tipsv1-s14", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from google/tipsv1-s14: direct link, hf CLI and curl.
- Browser
- Download file 222 MB
-
https://huggingface.co/google/tipsv1-s14/resolve/main/model.safetensors
- Command line
-
hf download hf://google/tipsv1-s14/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/google/tipsv1-s14/resolve/main/model.safetensors
222 MB
- Xet hash:
- 1190e1a5b5a1693acaf55b54eaee11e64e835326bfebdcf9a1b4966b9845cd21
- Size of remote file:
- 222 MB
- SHA256:
- 00348e7a167719469ee2dfc7c775bdc81b25ef2395fb48ef2beed4c91a095bf9
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