Instructions to use miladfa7/parsbert-base-sanay-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miladfa7/parsbert-base-sanay-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="miladfa7/parsbert-base-sanay-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("miladfa7/parsbert-base-sanay-uncased") model = AutoModelForMaskedLM.from_pretrained("miladfa7/parsbert-base-sanay-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03270bfa59f571d57c037ce7ff23c8cb3c98bec32240cd8e26ec0bce881cd512
- Size of remote file:
- 652 MB
- SHA256:
- b69a9daaa889427422770e8b1a48ef19c18ba401149a5a6739555efff6f91675
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.