Instructions to use hf-tiny-model-private/tiny-random-FlaubertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FlaubertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-FlaubertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2d4a30bcc635d459e05db1908512cf210da5c557a9328275fedd0e9df3490fd
- Size of remote file:
- 8.97 MB
- SHA256:
- 781cd1c3b27f710b635efb5a26ed997dcc5152e90c12f281c9f6d4225dc20a75
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