Instructions to use antoinelouis/camemberta-L8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antoinelouis/camemberta-L8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="antoinelouis/camemberta-L8")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("antoinelouis/camemberta-L8") model = AutoModel.from_pretrained("antoinelouis/camemberta-L8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e3af3b45094a029f906cf1fd5d40e56b507b178c21da00775969915da1c48b2
- Size of remote file:
- 334 MB
- SHA256:
- 10e886aa2a35f9e6d089ffe7f815dd71d7cb2a8d16f932c31d90278cb4f8b5f5
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