Instructions to use BaoNhan/mbert-vifn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaoNhan/mbert-vifn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaoNhan/mbert-vifn")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaoNhan/mbert-vifn") model = AutoModelForSequenceClassification.from_pretrained("BaoNhan/mbert-vifn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff6fd5c4df876d046c7beaea3dc598f0ce3bbbe1aff1245a8e14d3d55b7afbf2
- Size of remote file:
- 5.84 kB
- SHA256:
- 6feed46f424414d1657125d4227b096d7d5f1804bf62c1744e5fa2df72b24c76
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