Instructions to use EffyLi/bert-base-NER-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EffyLi/bert-base-NER-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EffyLi/bert-base-NER-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EffyLi/bert-base-NER-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("EffyLi/bert-base-NER-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EffyLi/bert-base-NER-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/EffyLi/bert-base-NER-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EffyLi/bert-base-NER-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EffyLi/bert-base-NER-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 067ed5dc0c710cc691ef73e1234238eab319727e0e24d9dc8566ed18d9fe32ca
- Size of remote file:
- 431 MB
- SHA256:
- 557dfeb88fe52996cbff8f4f4497ef46b25efb293652f100f8651d459b02bfb5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.