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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5eee64a2e1e26c8025b44ab0d9008edbca7a505db20eecaaf180b6d7ad194b6
- Size of remote file:
- 654 MB
- SHA256:
- 727beeb77f0902f609073e8ceaa9faaa65d42ae36d064a53c8d51bf05c29bdcc
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