Instructions to use minhdang14902/PhoBert_Edu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minhdang14902/PhoBert_Edu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minhdang14902/PhoBert_Edu")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minhdang14902/PhoBert_Edu") model = AutoModelForSequenceClassification.from_pretrained("minhdang14902/PhoBert_Edu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c697e56b16e0924d473e78440e3ac152902a6db41bd1e0497f37ef4a5b11c74
- Size of remote file:
- 541 MB
- SHA256:
- 9404b9ac68e26ab456ec0dcb3a8a1cff55d711e1bdd96389c390da863877f47f
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