Instructions to use hf-internal-testing/tiny-random-FlaubertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FlaubertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FlaubertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FlaubertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FlaubertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 407e675434545bf3a48f517870a4d8bb586fd98615b6ae8602b46978e6904e9b
- Size of remote file:
- 8.97 MB
- SHA256:
- d9042983e4fcb0a6b8859e76dc85db7d757ef5cf54d6e4e39371430a731cbf70
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