Instructions to use Nhat1904/mis_515_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nhat1904/mis_515_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nhat1904/mis_515_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nhat1904/mis_515_bert") model = AutoModelForSequenceClassification.from_pretrained("Nhat1904/mis_515_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ed49e9420faa79f0fa37604ab9398924ef768bebf19d796cf6b650e9cd64942
- Size of remote file:
- 3.39 kB
- SHA256:
- 54f97e8da2a2304906ce2101168ee97d84fbf9a225023c0d3a3bd6a52add8eb2
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