Instructions to use NTCAL/TrainedOnGPU_local_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTCAL/TrainedOnGPU_local_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTCAL/TrainedOnGPU_local_5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTCAL/TrainedOnGPU_local_5") model = AutoModelForSequenceClassification.from_pretrained("NTCAL/TrainedOnGPU_local_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a491867bbed57351d9d9442b3e3189030415d2d55039461f5c7d03f68b7f0770
- Size of remote file:
- 3.45 kB
- SHA256:
- 26da1ca94c648b166f1571c08fda1f83c0436208961ff37b7414f9520f3f2eec
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