Instructions to use antoinelouis/camembert-L2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antoinelouis/camembert-L2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="antoinelouis/camembert-L2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("antoinelouis/camembert-L2") model = AutoModel.from_pretrained("antoinelouis/camembert-L2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb1ed6acffe6771ee3d390083c78b4b185eee2fc75596035f3fe95c18c359c7d
- Size of remote file:
- 159 MB
- SHA256:
- f5f0b6fd28ca31585427ec20f9651d8f17d7c4d9b8e842a46ebe7c6d5dc16c8a
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