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")# pip install -U transformers accelerate # 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
Download training_args.bin from migueladarlo/distilbert-depression-base: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/migueladarlo/distilbert-depression-base/resolve/main/training_args.bin
- Command line
-
hf download hf://migueladarlo/distilbert-depression-base/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/migueladarlo/distilbert-depression-base/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- e7b2b6953dd44348cf6cd5b1fa29e4e56b15c7adb65552d061bb1dd480ba01b9
- Size of remote file:
- 2.86 kB
- SHA256:
- 0d35c7b82aa10f98dd2f2a2951c6b358aa639e82fd29d323cc8fcc59a2aeeb3d
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