Instructions to use HooshvareLab/bert-base-parsbert-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-base-parsbert-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HooshvareLab/bert-base-parsbert-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-base-parsbert-uncased") model = AutoModelForMaskedLM.from_pretrained("HooshvareLab/bert-base-parsbert-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01108b3eccc7689a7bf7562e925823f12f640b42186b03dfb0cf69f748aaa90e
- Size of remote file:
- 652 MB
- SHA256:
- 2bcf6b7f3e82ff7fd6873e2cfe2802337bae4a183025da9243a217e4c153e519
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.