Instructions to use insaf/Flaubert-DA_Augmentation-v-0-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use insaf/Flaubert-DA_Augmentation-v-0-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="insaf/Flaubert-DA_Augmentation-v-0-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("insaf/Flaubert-DA_Augmentation-v-0-2") model = AutoModelForSequenceClassification.from_pretrained("insaf/Flaubert-DA_Augmentation-v-0-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 175210d734e3a661d3b8aa9feb4d71288b329fd0690eecdc382a1c7b0e8da977
- Size of remote file:
- 549 MB
- SHA256:
- 3897a00b3946ce1b29b7db87df9177484a708643ef3b4b10ab5eec99d7f48649
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