Instructions to use Fsoft-AIC/dopamin-python-developmentnotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-python-developmentnotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-python-developmentnotes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-python-developmentnotes") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-python-developmentnotes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1af9e500a26a837008d81a422091db6b8c07fc91abd5e05aa2bee4c0930d5010
- Size of remote file:
- 14.5 kB
- SHA256:
- 81b6b0ab2251b3d4320e396050c542bb442b41cd8fa0848792b9aaa47941f3aa
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