Instructions to use Treether/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Treether/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Treether/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Treether/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Treether/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Treether/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/Treether/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Treether/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Treether/bert-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- c7722d96b7a62b264d699a592cebefdbc421873e267839e0e5e7c9a2e7f45bcc
- Size of remote file:
- 431 MB
- SHA256:
- facf32fa11e61adcf92bc8468006b48c5fe5c68e1a0b06cd5fabdf96ea6b0041
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