Instructions to use bdpc/test_twowayloss_implementation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bdpc/test_twowayloss_implementation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bdpc/test_twowayloss_implementation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bdpc/test_twowayloss_implementation") model = AutoModelForSequenceClassification.from_pretrained("bdpc/test_twowayloss_implementation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de5fcb7a53fef3ba85df3c59653473135a562eb97cc3cf7fa8851b7dac5934b2
- Size of remote file:
- 4.16 kB
- SHA256:
- 757bd5925bae31ae22f37638e83124baca0f48d547ca3d9341caca7a5068f50c
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