Fill-Mask
Transformers
PyTorch
English
caduceus
DNA
genomics
fish
Caduceus
masked-language-model
nucleotide-modeling
foundation-model
reverse-complement
custom-code
FishCaduceus
custom_code
Instructions to use FishCaduceus/FishCaduceus-28L-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FishCaduceus/FishCaduceus-28L-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FishCaduceus/FishCaduceus-28L-512", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("FishCaduceus/FishCaduceus-28L-512", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43749c15fca2d72a6258a707f3d9c7d4cb6ff62ce5885481317d93ccc5cc3988
- Size of remote file:
- 449 MB
- SHA256:
- 68c3d0a6dfd644e9c3d2568040801a5d4acb8e14d1ef442c1e4febe1cb1c4eba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.