Instructions to use NTCAL/cudaTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTCAL/cudaTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTCAL/cudaTest")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTCAL/cudaTest") model = AutoModelForSequenceClassification.from_pretrained("NTCAL/cudaTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9270ad87be27bf90d86e3455de5969ff63f7427aa698bd8d18477d4a36ea53f6
- Size of remote file:
- 3.45 kB
- SHA256:
- 6a812ee33718a65dab830a862598b733c2b6cc90a9e795e4336854d64eaf0614
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