Instructions to use insaf/Flaubert-DA_initial_no_Augmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use insaf/Flaubert-DA_initial_no_Augmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="insaf/Flaubert-DA_initial_no_Augmentation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("insaf/Flaubert-DA_initial_no_Augmentation") model = AutoModelForSequenceClassification.from_pretrained("insaf/Flaubert-DA_initial_no_Augmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81dd27f53629b367fcf1423bee0deba770091321fe9519f4fa87433ec67bd0ee
- Size of remote file:
- 549 MB
- SHA256:
- 58980d40d1dd263250de0ec3624204c90de6b6841b851a08337981a1bbb4de47
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