Instructions to use ybelkada/tiny-random-flava with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ybelkada/tiny-random-flava with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ybelkada/tiny-random-flava")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("ybelkada/tiny-random-flava") model = AutoModel.from_pretrained("ybelkada/tiny-random-flava", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ybelkada/tiny-random-flava: direct link, hf CLI and curl.
- Browser
- Download file 773 kB
-
https://huggingface.co/ybelkada/tiny-random-flava/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ybelkada/tiny-random-flava/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ybelkada/tiny-random-flava/resolve/main/pytorch_model.bin
773 kB
- Xet hash:
- 5483ff15c8d2e2595c80a24a6b1d45e4d94e304fd4af5b4f612e4d6ab18eed4b
- Size of remote file:
- 773 kB
- SHA256:
- 6a25c4853f0bbd0db7114503b4e41d24305189cc288e3c02a8a0ab0dec992e39
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