Instructions to use harish/PT-v3-dev-test-all-PreTrain-e10-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-v3-dev-test-all-PreTrain-e10-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/PT-v3-dev-test-all-PreTrain-e10-all")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e10-all") model = AutoModelForMaskedLM.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e10-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7baa01221b5444eba32fd39cdd6fed7fb7d0eeb4da28147e0b5f2c5295459b6
- Size of remote file:
- 712 MB
- SHA256:
- b85c2d1261d6d1e22dd10361768251c00314efc9e79c45b3831db896fca8b3d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.