Instructions to use dumitrescustefan/bert-base-romanian-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dumitrescustefan/bert-base-romanian-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dumitrescustefan/bert-base-romanian-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dumitrescustefan/bert-base-romanian-ner") model = AutoModelForTokenClassification.from_pretrained("dumitrescustefan/bert-base-romanian-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dumitrescustefan/bert-base-romanian-ner: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/dumitrescustefan/bert-base-romanian-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dumitrescustefan/bert-base-romanian-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dumitrescustefan/bert-base-romanian-ner/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- d10b125237cde33f621c8792c2b55992d91a0703d0959df07a2dac2ed9bf4841
- Size of remote file:
- 496 MB
- SHA256:
- 3f454ae05cb7ad56165557beb0cc57ba2d638938215571cf61c2d94df502bb20
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.