Instructions to use Arvnd03/FirstTry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arvnd03/FirstTry with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arvnd03/FirstTry")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arvnd03/FirstTry") model = AutoModelForSequenceClassification.from_pretrained("Arvnd03/FirstTry", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 971bb322e5d41d3cd8189b44b112a2c13abeae16e6046e3460cfa18275c18f9a
- Size of remote file:
- 3.45 kB
- SHA256:
- f1153057c5d6aa9b79f8ad9bb2c6e01114c3c8018e1813784f13823f72f65b56
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