Instructions to use Aleksandar/distilbert-srb-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aleksandar/distilbert-srb-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Aleksandar/distilbert-srb-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Aleksandar/distilbert-srb-ner") model = AutoModelForTokenClassification.from_pretrained("Aleksandar/distilbert-srb-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5642d159173f581f73a30890b68b6ddfc0611ee0892cbca0a229d09790ffac8a
- Size of remote file:
- 326 MB
- SHA256:
- 428067294de68a01e6ad5572659ee165a1bc5f85d0eadc54cbb0d054fb72830a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.