Instructions to use Sudarshan00/Ms_Marcoasksciencemodeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sudarshan00/Ms_Marcoasksciencemodeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Sudarshan00/Ms_Marcoasksciencemodeling")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Sudarshan00/Ms_Marcoasksciencemodeling") model = AutoModelForMaskedLM.from_pretrained("Sudarshan00/Ms_Marcoasksciencemodeling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b843be83d32afdd88c70b01e6c27d520d830e4796f4d1d3c5d302e39c18f6bf8
- Size of remote file:
- 499 MB
- SHA256:
- e3237a9d7135489006c77a3cd6d4926de1ec97b7809cdff8b7bd9349c66d3857
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.