Instructions to use simecek/ArabidopsisDNADeberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/ArabidopsisDNADeberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/ArabidopsisDNADeberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/ArabidopsisDNADeberta") model = AutoModelForMaskedLM.from_pretrained("simecek/ArabidopsisDNADeberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73393b3b1e537fdb71dc0c8cfa99f97911f7151e32053bb75d699a39823b924a
- Size of remote file:
- 3.25 kB
- SHA256:
- 7d6a81286add1694f9a5bb601414c59ef1f92572f9b586e8edfd0988a6d44587
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.