Instructions to use ahmedoumar/my_ner_MARBERTv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedoumar/my_ner_MARBERTv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ahmedoumar/my_ner_MARBERTv2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ahmedoumar/my_ner_MARBERTv2") model = AutoModelForTokenClassification.from_pretrained("ahmedoumar/my_ner_MARBERTv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ahmedoumar/my_ner_MARBERTv2: direct link, hf CLI and curl.
- Browser
- Download file 649 MB
-
https://huggingface.co/ahmedoumar/my_ner_MARBERTv2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ahmedoumar/my_ner_MARBERTv2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ahmedoumar/my_ner_MARBERTv2/resolve/main/pytorch_model.bin
649 MB
- Xet hash:
- 5f5d031bdcba7ef611f0d1d1be809fef1c84cd105d59dcb76b7b7c88c9f4d7d0
- Size of remote file:
- 649 MB
- SHA256:
- 851b4cba8dc5655737f4808de0da859d8546d772be2c858547fac14aed37e032
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