Instructions to use HooshvareLab/bert-base-parsbert-peymaner-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-base-parsbert-peymaner-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-base-parsbert-peymaner-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-base-parsbert-peymaner-uncased") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-base-parsbert-peymaner-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4415bdfbed9e806a8853f2ee2b9d91bd2758242674e67a92beada038d831e448
- Size of remote file:
- 649 MB
- SHA256:
- e46a69d668b07724c7b135207c1d5ec0f2b838c010991445fc3eaf1e7b857f69
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