Instructions to use Resume-screener/distil-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Resume-screener/distil-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Resume-screener/distil-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Resume-screener/distil-bert") model = AutoModelForSequenceClassification.from_pretrained("Resume-screener/distil-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fbfeec760a2c083b7766736537a171af1b164e0be1b87a3ffb4873a64d9c242
- Size of remote file:
- 320 kB
- SHA256:
- 9d2f5ec9fe1cdf6b709cc3bcf746e82788ee3561f1f659a9bc94dadcd7648225
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