Instructions to use davidcechak/DNADeberta_fine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidcechak/DNADeberta_fine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidcechak/DNADeberta_fine")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidcechak/DNADeberta_fine") model = AutoModelForSequenceClassification.from_pretrained("davidcechak/DNADeberta_fine", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from davidcechak/DNADeberta_fine: direct link, hf CLI and curl.
- Browser
- Download file 357 MB
-
https://huggingface.co/davidcechak/DNADeberta_fine/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://davidcechak/DNADeberta_fine/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/davidcechak/DNADeberta_fine/resolve/main/pytorch_model.bin
357 MB
- Xet hash:
- 05ae21f32844871dd68f045ecc4d04962a5294e052bc1e2d12b71ec95c3a2140
- Size of remote file:
- 357 MB
- SHA256:
- 670a02f748b30a4bea879bca7adaace493c63301927390e1f7d78e6c2546c065
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