Instructions to use deepmind/vision-perceiver-learned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepmind/vision-perceiver-learned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="deepmind/vision-perceiver-learned") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("deepmind/vision-perceiver-learned") model = AutoModelForImageClassification.from_pretrained("deepmind/vision-perceiver-learned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.a52f2ed
-
Update config.json
e3d8bac
-
Update README.md
8292664 -
Create README.md
450498e -
Upload preprocessor_config.json
4c837f1
-
Update P model
f19dc2a
-
Update PyTorch model
8c4f501
-
Add config file
6c5304e -
Add model file
d3c5c3b -
initial commit
9265e3c