Instructions to use tr-aravindan/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr-aravindan/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tr-aravindan/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tr-aravindan/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("tr-aravindan/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from tr-aravindan/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/tr-aravindan/bert-finetuned-ner/resolve/main/tf_model.h5
- Command line
-
hf download hf://tr-aravindan/bert-finetuned-ner/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/tr-aravindan/bert-finetuned-ner/resolve/main/tf_model.h5
431 MB
- Xet hash:
- 74ec5cd34f66d5d6f357acfd4ac1c25c1616a57bea1bb623fb23b32545483cb4
- Size of remote file:
- 431 MB
- SHA256:
- 0a1e6e00ee3e6fbc4d363498f9c375bfc7a3350ec1ceaf6685ab720b81330385
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