Instructions to use Pra-tham/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pra-tham/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pra-tham/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pra-tham/results") model = AutoModelForSequenceClassification.from_pretrained("Pra-tham/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52ff7560feadd84d085922a574217bd0425f8ae3374a104cc7e2ea038d1db8be
- Size of remote file:
- 5.11 kB
- SHA256:
- 748815ce4ceb09fa682583f72e0042c644a4a404f000681ae3fae27f0c533f7d
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