Instructions to use Vlasta/DNADebertaSentencepiece10k_continuation_continuation_continuation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vlasta/DNADebertaSentencepiece10k_continuation_continuation_continuation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Vlasta/DNADebertaSentencepiece10k_continuation_continuation_continuation")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Vlasta/DNADebertaSentencepiece10k_continuation_continuation_continuation") model = AutoModelForMaskedLM.from_pretrained("Vlasta/DNADebertaSentencepiece10k_continuation_continuation_continuation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3cc908b9a01f7e1bbc168db41fb646b650acdd863bf4c0ea3c1bbf49e709ef0
- Size of remote file:
- 205 MB
- SHA256:
- 2255f60bccd9ce407550350f4f82e2c89388ce540e89ad89da24c87c45b53a0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.