Instructions to use Taykhoom/mRNA-FM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/mRNA-FM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/mRNA-FM", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/mRNA-FM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57b7043e3cb77492c1ff021d2850e082d9a112fec9aa613ef7f2d1b4138e85c8
- Size of remote file:
- 957 MB
- SHA256:
- 33d9243386d47b34cde21ddb5d41fc410cef22542d2dc50bf4dfa0ed9ae24de4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.