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
Commit History
-
Training in progress, step 320000
e34c774 -
Training in progress, step 300000
2798e9a -
Training in progress, step 280000
65b133c -
Training in progress, step 260000
7ea8963
-
Training in progress, step 240000
4be98a0 -
Training in progress, step 220000
fab5776 -
Training in progress, step 200000
3b3a62a -
Training in progress, step 180000
c80adc9
-
Training in progress, step 160000
e6f26b1 -
Training in progress, step 140000
8763df6 -
Training in progress, step 120000
13ed335
-
Training in progress, step 100000
81db3dc -
Training in progress, step 80000
31ae596 -
Training in progress, step 60000
d107d18 -
Training in progress, step 40000
78cfc3e
-
Training in progress, step 20000
38e2825 -
initial commit
bdd96d3