Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
French
camembert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use baptiste-pasquier/camembert-allocine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baptiste-pasquier/camembert-allocine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="baptiste-pasquier/camembert-allocine")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("baptiste-pasquier/camembert-allocine") model = AutoModelForSequenceClassification.from_pretrained("baptiste-pasquier/camembert-allocine", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 567090dee38b232d05b0884d2444cd0f50ff1dc61beff8ce6ede69c81a1c924a
- Size of remote file:
- 443 MB
- SHA256:
- 2fb56261d3f2b4685da2b6fa1c0ba1a6b899cefae578120d5d229f5c4023dc4f
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