Instructions to use rmihaylov/bert-base-ner-theseus-bg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rmihaylov/bert-base-ner-theseus-bg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rmihaylov/bert-base-ner-theseus-bg")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rmihaylov/bert-base-ner-theseus-bg") model = AutoModelForTokenClassification.from_pretrained("rmihaylov/bert-base-ner-theseus-bg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rmihaylov/bert-base-ner-theseus-bg: direct link, hf CLI and curl.
- Browser
- Download file 539 MB
-
https://huggingface.co/rmihaylov/bert-base-ner-theseus-bg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rmihaylov/bert-base-ner-theseus-bg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rmihaylov/bert-base-ner-theseus-bg/resolve/main/pytorch_model.bin
539 MB
- Xet hash:
- 0687ebbda5c18eeafc0ace96e3a48f0081cc36862e2b52c63e17550e4d86126b
- Size of remote file:
- 539 MB
- SHA256:
- 135b66bd60a7fb30ab9eef7fb41976455f9fbb006a754ff0592e142221f45f38
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