Instructions to use Apv/Flaubert_1619 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apv/Flaubert_1619 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Apv/Flaubert_1619")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Apv/Flaubert_1619") model = AutoModelForSequenceClassification.from_pretrained("Apv/Flaubert_1619") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15cfa8769b2145e258dfbf2a23e2f1dd30b06754c2c9b5caf579db4462e923a6
- Size of remote file:
- 553 MB
- SHA256:
- 745f504f44793ca36929e71584783ee18bc553e45a74cf0c0a69737b5bff91ca
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