Instructions to use Amir13/xlm-roberta-base-fa-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amir13/xlm-roberta-base-fa-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Amir13/xlm-roberta-base-fa-base-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Amir13/xlm-roberta-base-fa-base-ner") model = AutoModelForTokenClassification.from_pretrained("Amir13/xlm-roberta-base-fa-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Amir13/xlm-roberta-base-fa-base-ner: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Amir13/xlm-roberta-base-fa-base-ner/resolve/main/tokenizer.json
- Command line
-
hf download hf://Amir13/xlm-roberta-base-fa-base-ner/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Amir13/xlm-roberta-base-fa-base-ner/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 0717d4742b537134c3af481bedb40759b23c535633b0552db10818f68c187f09
- Size of remote file:
- 17.1 MB
- SHA256:
- 1edb0658cb47689db5cf78194ebe041bba3b6b775d1f1069fc9501b372d4acb0
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