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:
- c6ee663734b2f185a88efe1182a677e0129f801c062ee7f8b45ddf936e8f3b03
- Size of remote file:
- 1.42 GB
- SHA256:
- 0212d2f5ba696f1a291f4b6b63be1c40847e0a747f641ea5c0f86d7cd65cc938
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