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:
- 07b0b7561e0c1bd3bd1d549690c8ce12c16a80cace85551e3c7d490bc6ea29bb
- Size of remote file:
- 499 MB
- SHA256:
- cc9814a8421322ffc85750a80b1eddae15a448f6cf29a1e8b5be1f9cb63d1917
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