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:
- 9a91927002bbd07c94ff3520cd2c4eaa033451cc98800ff700debc635674eee7
- Size of remote file:
- 357 MB
- SHA256:
- 8b168c7deb33770fb836d2ffd44df5a181f227121701025b291324ce9c0a41b0
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