Instructions to use zagibest/roberta-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zagibest/roberta-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="zagibest/roberta-base-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("zagibest/roberta-base-ner") model = AutoModelForTokenClassification.from_pretrained("zagibest/roberta-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zagibest/roberta-base-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/zagibest/roberta-base-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://zagibest/roberta-base-ner/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/zagibest/roberta-base-ner/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 666326b22e1aa9bb2d12666d116016d5df2447ab23de7f571651dc273479a01f
- Size of remote file:
- 3.52 kB
- SHA256:
- 907cfbefa74c3b0f54f16a77f3b4426a20f5a47dd1cc73894d7b3ca8465473bb
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