Instructions to use MuhammedSaeed/RobertaPCM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MuhammedSaeed/RobertaPCM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MuhammedSaeed/RobertaPCM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MuhammedSaeed/RobertaPCM") model = AutoModelForMaskedLM.from_pretrained("MuhammedSaeed/RobertaPCM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 825754a04a231b01e0df42391e6c91f7b5480a328706a68b603dd2291a46515d
- Size of remote file:
- 998 MB
- SHA256:
- a0ef99498453a2b5f14a1a057d288e79ac64a46e6e3a3dc077deccef485cd6ba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.