Instructions to use yidi-huang/bert-finetuned-ner-lieu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yidi-huang/bert-finetuned-ner-lieu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yidi-huang/bert-finetuned-ner-lieu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yidi-huang/bert-finetuned-ner-lieu") model = AutoModelForTokenClassification.from_pretrained("yidi-huang/bert-finetuned-ner-lieu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from yidi-huang/bert-finetuned-ner-lieu: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/yidi-huang/bert-finetuned-ner-lieu/resolve/main/tf_model.h5
- Command line
-
hf download hf://yidi-huang/bert-finetuned-ner-lieu/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/yidi-huang/bert-finetuned-ner-lieu/resolve/main/tf_model.h5
440 MB
- Xet hash:
- f6be1502dde888900c1866495d57070bf1877d3bc6d60655af1ee094fa1a4ae1
- Size of remote file:
- 440 MB
- SHA256:
- c15f0a53a1515aaa53fe832a7ddc476f9b6661fe3a1c957457dbf241fef52707
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