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:
- 7bffefc02abafb7de99792bbc3a8502fed84b64fe338831d9d261a684f176b25
- Size of remote file:
- 499 MB
- SHA256:
- db9369605de6d76ac21327786351e2e4e07c385819e864dcaef940817f5f9ffd
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