Instructions to use migueladarlo/distilbert-depression-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use migueladarlo/distilbert-depression-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="migueladarlo/distilbert-depression-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("migueladarlo/distilbert-depression-base") model = AutoModelForSequenceClassification.from_pretrained("migueladarlo/distilbert-depression-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d596d2701ce38b19d7b7c431603df4be88911fa24a3358e454985c3b3c351911
- Size of remote file:
- 268 MB
- SHA256:
- f0b4e3eaaf38a17796e390dfa7ebb0b872a61fea569acb303f27b2d0c7acc1cb
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