Instructions to use hts98/classification_phobert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/classification_phobert-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hts98/classification_phobert-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hts98/classification_phobert-v2") model = AutoModelForSequenceClassification.from_pretrained("hts98/classification_phobert-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b19c1153a3d174952a15d273788e4c705c63e4473da6cc328614a0d9d13a879c
- Size of remote file:
- 5.43 kB
- SHA256:
- 09f214f8a373b189714042623d18e33c8cbb1642f63be5a97242316c2dbdbcbb
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