Instructions to use Davlan/bert-base-multilingual-cased-ner-hrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/bert-base-multilingual-cased-ner-hrl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Davlan/bert-base-multilingual-cased-ner-hrl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl") model = AutoModelForTokenClassification.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
927df9c | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:8c707863b713df859962ba50dcd834ab1b5bd459e7cc184e3aab62f2d34fc764
size 709167607
|