Instructions to use HooshvareLab/bert-base-parsbert-ner-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/bert-base-parsbert-ner-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/bert-base-parsbert-ner-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-base-parsbert-ner-uncased") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/bert-base-parsbert-ner-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from HooshvareLab/bert-base-parsbert-ner-uncased: direct link, hf CLI and curl.
- Browser
- Download file 652 MB
-
https://huggingface.co/HooshvareLab/bert-base-parsbert-ner-uncased/resolve/main/tf_model.h5
- Command line
-
hf download hf://HooshvareLab/bert-base-parsbert-ner-uncased/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/HooshvareLab/bert-base-parsbert-ner-uncased/resolve/main/tf_model.h5
652 MB
- Xet hash:
- 216f9d80df37e1f75e15ff6d38574fb66766c54f51b20395d6dd1fd8b8dbf5f2
- Size of remote file:
- 652 MB
- SHA256:
- 0741ffadcc1fa34f6e4264a01b8cee5dd5a8115fa3fe0db7113773e707e90e30
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