Instructions to use simecek/DNADeberta2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/DNADeberta2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/DNADeberta2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/DNADeberta2") model = AutoModelForMaskedLM.from_pretrained("simecek/DNADeberta2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simecek/DNADeberta2: direct link, hf CLI and curl.
- Browser
- Download file 187 MB
-
https://huggingface.co/simecek/DNADeberta2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://simecek/DNADeberta2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simecek/DNADeberta2/resolve/main/pytorch_model.bin
187 MB
- Xet hash:
- 2a396635fc1fe044be638cc945022808c3a3b1a48b4e10183a547c1c920971b1
- Size of remote file:
- 187 MB
- SHA256:
- 9642d46c3d4e28690107e45822ea8f19e0602da5824481a82ccdc24d30c5a167
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