Instructions to use thanhduycao/model_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thanhduycao/model_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thanhduycao/model_v5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thanhduycao/model_v5") model = AutoModelForSequenceClassification.from_pretrained("thanhduycao/model_v5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cab40e739ddd744c54c54b60ae42e96edad97030f89dabe102729cb9d7032192
- Size of remote file:
- 90.9 MB
- SHA256:
- 9d55e528cc28f8bc42d9fd3fd194cea1252bbdc07e10b70b48d3920880bd4938
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