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:
- d77d63528145f3b90370a511c022c45db5d3e7a005eebcb6e7007bb5a5a51bff
- Size of remote file:
- 4.34 kB
- SHA256:
- 11cafebf9be52acb2504b6cfb5c414f0faf57c8f9b6c67b9a86b0a5ba25ba4d6
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