Instructions to use Andrija/SRoBERTa-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrija/SRoBERTa-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Andrija/SRoBERTa-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Andrija/SRoBERTa-NER") model = AutoModelForTokenClassification.from_pretrained("Andrija/SRoBERTa-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Andrija/SRoBERTa-NER: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/Andrija/SRoBERTa-NER/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Andrija/SRoBERTa-NER@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Andrija/SRoBERTa-NER/resolve/refs%2Fpr%2F1/training_args.bin
2.61 kB
- Xet hash:
- 50018b69796ab0bd860b525a7786844ec7f73058558630ec8528ee78aff22a31
- Size of remote file:
- 2.61 kB
- SHA256:
- 20a5db44f91966a987ef7fcaa2ae411f4058316bea657a9d78a29e29587ccca7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.