Instructions to use Taykhoom/CodonBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/CodonBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/CodonBERT", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/CodonBERT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db2a5d3a18312cc0decc3659c84d8763c52b66450cb61e653337179dfd1024d9
- Size of remote file:
- 346 MB
- SHA256:
- 203e1dbf3aa7b7c038b25998b8fed977245361e85ded0a08184d80d8eb809898
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.