Instructions to use Sid8421/tinybert-depression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sid8421/tinybert-depression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sid8421/tinybert-depression")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sid8421/tinybert-depression") model = AutoModelForSequenceClassification.from_pretrained("Sid8421/tinybert-depression") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97705f3b3597f7593fcf70a33b8195d2a4388746b41e4842b30a2510f239339e
- Size of remote file:
- 57.4 MB
- SHA256:
- 180afa3104253c3ee30dd89507599df655df227ec61ff329f7c2d4bfe52dff14
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