Instructions to use brad1141/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brad1141/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brad1141/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brad1141/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("brad1141/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from brad1141/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 592 MB
-
https://huggingface.co/brad1141/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://brad1141/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/brad1141/bert-finetuned-ner/resolve/main/pytorch_model.bin
592 MB
- Xet hash:
- c92f4b4dba719d42a0296244ec37fc97c0b294f02c99c6a5b2af191af93de17d
- Size of remote file:
- 592 MB
- SHA256:
- 9f01e986c6e41f5df40f8d8a7724cbb444306a0906a83006e6b48d623c3e8f32
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