Instructions to use RonTon05/PhoBert_content_256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RonTon05/PhoBert_content_256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RonTon05/PhoBert_content_256")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RonTon05/PhoBert_content_256") model = AutoModelForSequenceClassification.from_pretrained("RonTon05/PhoBert_content_256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81475b3abbb7d205abf85dc3984de76abb14cf2166824066c6447df10615bcfc
- Size of remote file:
- 5.65 kB
- SHA256:
- a7cf2cc5329ef902f937104abf9ea4d525d2a72e43f696be066a45a9c062fb73
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