Instructions to use nvidia/groupvit-gcc-redcaps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/groupvit-gcc-redcaps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nvidia/groupvit-gcc-redcaps")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("nvidia/groupvit-gcc-redcaps") model = AutoModel.from_pretrained("nvidia/groupvit-gcc-redcaps", 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.5977a9b
-
Add red_caps tag
9219591
-
Create README.md
518d977
-
Upload preprocessor_config.json
aa3d736 -
Upload tokenizer_config.json
8911670 -
Upload special_tokens_map.json
c2c96f5 -
Upload vocab.json
13162b7 -
Upload vocab.json
648794e -
Upload merges.txt
754d533 -
Upload tokenizer.json
ecb2bd0 -
add model
57edee6 -
initial commit
1c72a26