Instructions to use hatmimoha/arabic-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hatmimoha/arabic-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hatmimoha/arabic-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hatmimoha/arabic-ner") model = AutoModelForTokenClassification.from_pretrained("hatmimoha/arabic-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from hatmimoha/arabic-ner: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/hatmimoha/arabic-ner/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://hatmimoha/arabic-ner/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/hatmimoha/arabic-ner/resolve/main/flax_model.msgpack
440 MB
- Xet hash:
- 04f615640fc409754fd77b4cd7875c44ee0211e0ff258b262af0b9f8ecd51c1e
- Size of remote file:
- 440 MB
- SHA256:
- a744745bcb0b1427238607d692de80c881cf6362517191bcc1f36ad8e5aafad0
ยท
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