Instructions to use davidcechak/DNADebertaK8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidcechak/DNADebertaK8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="davidcechak/DNADebertaK8b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("davidcechak/DNADebertaK8b") model = AutoModelForMaskedLM.from_pretrained("davidcechak/DNADebertaK8b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from davidcechak/DNADebertaK8b: direct link, hf CLI and curl.
- Browser
- Download file 388 MB
-
https://huggingface.co/davidcechak/DNADebertaK8b/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://davidcechak/DNADebertaK8b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/davidcechak/DNADebertaK8b/resolve/main/pytorch_model.bin
388 MB
- Xet hash:
- 83aa3d18d270cc2912ea04e2b9ed9a3d1e1bad33dc1fff59325afa241fcd732c
- Size of remote file:
- 388 MB
- SHA256:
- c8e809fc2f24f9bf214b95e50737705ea22a0d001bfe105dcd163a36923bc2a3
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