Instructions to use Andrija/SRoBERTa-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrija/SRoBERTa-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Andrija/SRoBERTa-base-NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Andrija/SRoBERTa-base-NER") model = AutoModelForTokenClassification.from_pretrained("Andrija/SRoBERTa-base-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Andrija/SRoBERTa-base-NER: direct link, hf CLI and curl.
- Browser
- Download file 319 MB
-
https://huggingface.co/Andrija/SRoBERTa-base-NER/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Andrija/SRoBERTa-base-NER/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Andrija/SRoBERTa-base-NER/resolve/main/pytorch_model.bin
319 MB
- Xet hash:
- 94a9fcfb6e78cf373fddfe78a6d2aec8512b8933a2a0c8ee6399d570b1b8c470
- Size of remote file:
- 319 MB
- SHA256:
- 5fa8c4c7d8d3144728c9d78b41aaa637b23fe45e8042e30220bdc885168e59e6
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