Instructions to use dd3434/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dd3434/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dd3434/test_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dd3434/test_model") model = AutoModelForSequenceClassification.from_pretrained("dd3434/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bda7fd1b6b215527b87a9b3cfa741af2a8703219d52fd6e3440c75fc0d6856e2
- Size of remote file:
- 443 MB
- SHA256:
- 8cd70296f1efb94b624df1a75f4c3f3da03909fcd5680fee6f73cae37b15422f
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