Instructions to use zhihan1996/DNABERT-S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhihan1996/DNABERT-S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zhihan1996/DNABERT-S", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zhihan1996/DNABERT-S", trust_remote_code=True) model = AutoModel.from_pretrained("zhihan1996/DNABERT-S", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2148a698b7f4d34759bb80675dc934b1be30a04c92675f2099936ee1efba1a7a
- Size of remote file:
- 468 MB
- SHA256:
- f3cfc3d0541859df64759e758cc4bc40fe1d5760799a7d098a9f9f09501c1e5f
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