Instructions to use Fsoft-AIC/dopamin-python-usage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-python-usage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-python-usage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-python-usage") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-python-usage") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cd59556543150b21b408d1a71e706830437276fa77acb0eefd4141bc8b781f9
- Size of remote file:
- 612 MB
- SHA256:
- d0da165d15bcf5369c61724f11af7792194f48c9ec4759e3328b6c2612a1f6db
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