Token Classification
Transformers
Safetensors
Azerbaijani
bert
ner
multilingual
azerbaijani
Eval Results (legacy)
Instructions to use ismatsamadov/mbert-az-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ismatsamadov/mbert-az-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ismatsamadov/mbert-az-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ismatsamadov/mbert-az-ner") model = AutoModelForTokenClassification.from_pretrained("ismatsamadov/mbert-az-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ismatsamadov/mbert-az-ner: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/ismatsamadov/mbert-az-ner/resolve/main/model.safetensors
- Command line
-
hf download hf://ismatsamadov/mbert-az-ner/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ismatsamadov/mbert-az-ner/resolve/main/model.safetensors
709 MB
- Xet hash:
- b02812ea118b9333d86f34d53ef39cf6c9345a8b9a229a3ca0187eeec8b077d3
- Size of remote file:
- 709 MB
- SHA256:
- df9bcc2cb183cbf505208e71cfc23015faef4f3bacab9190c59f77a33a8b2a8b
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