Instructions to use davidcechak/DNADebertaK8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidcechak/DNADebertaK8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="davidcechak/DNADebertaK8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("davidcechak/DNADebertaK8") model = AutoModelForMaskedLM.from_pretrained("davidcechak/DNADebertaK8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from davidcechak/DNADebertaK8: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/davidcechak/DNADebertaK8/resolve/main/training_args.bin
- Command line
-
hf download hf://davidcechak/DNADebertaK8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/davidcechak/DNADebertaK8/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 8f2adf57a7f2e1c641ed669c98ff440c370bd0d85fbdee1617f051b03c1f3709
- Size of remote file:
- 3.31 kB
- SHA256:
- 5bca75a3172580913587cbe05d5a69efad904894d474e6813f28a01d285ec9cd
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