Instructions to use QMMMS/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QMMMS/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="QMMMS/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("QMMMS/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("QMMMS/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from QMMMS/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/QMMMS/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://QMMMS/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/QMMMS/bert-finetuned-ner/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 819266f085dc93a9b9f4a2b8d2355fb3b82e10b4d8fbe027bdcef8549800cec5
- Size of remote file:
- 4.92 kB
- SHA256:
- 57ef05348f86ff90b13848cbfe80a81d9ee304207cdc1be88783fd947bdd54fa
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