Instructions to use MM2157/BERT_token_classification_AraEval24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MM2157/BERT_token_classification_AraEval24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MM2157/BERT_token_classification_AraEval24")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MM2157/BERT_token_classification_AraEval24") model = AutoModelForTokenClassification.from_pretrained("MM2157/BERT_token_classification_AraEval24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MM2157/BERT_token_classification_AraEval24: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/MM2157/BERT_token_classification_AraEval24/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MM2157/BERT_token_classification_AraEval24/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MM2157/BERT_token_classification_AraEval24/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 9b735da842cfa7c4fa7d115576328eef65b146f7992c0aaf6bc10ba7f7900539
- Size of remote file:
- 436 MB
- SHA256:
- 49eea737b290e6d8b73fb97836ebcfb13a7a1c9f9b3b0ece7e656994ffe996fa
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