Instructions to use antoinelouis/camembert-L8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antoinelouis/camembert-L8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="antoinelouis/camembert-L8")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("antoinelouis/camembert-L8") model = AutoModel.from_pretrained("antoinelouis/camembert-L8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0fc4acd813927a4ac7a9743fb68251ca4a38825b989898264418916f382779f
- Size of remote file:
- 329 MB
- SHA256:
- 1b3ee39722de750b63cae40a09bfd588d8e3240c731d37533d8d88d29931f90a
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