Feature Extraction
Transformers
PyTorch
TensorBoard
Safetensors
French
deberta-v2
deberta
deberta-v3
text-embeddings-inference
Instructions to use almanach/camemberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camemberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="almanach/camemberta-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("almanach/camemberta-base") model = AutoModel.from_pretrained("almanach/camemberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fc3a4072a14327eb4591d54e7a5237eef113363358090e09ab469d86d6143d9
- Size of remote file:
- 447 MB
- SHA256:
- ae6d1d5495d283736fbf8808c8177c364638abfef16c20f3d4a65683ef42f23e
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