Instructions to use HooshvareLab/roberta-fa-zwnj-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HooshvareLab/roberta-fa-zwnj-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HooshvareLab/roberta-fa-zwnj-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/roberta-fa-zwnj-base-ner") model = AutoModelForTokenClassification.from_pretrained("HooshvareLab/roberta-fa-zwnj-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5c2be9b67542967079f220bf2cb4e649dad97fff49c9b56360b914a5e36bcad
- Size of remote file:
- 471 MB
- SHA256:
- 12b5dbde0fd2e2cdabb99cf07b95d241643031398bbd310cf7bdf1adaf86239f
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