Instructions to use pczarnik/herbert-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pczarnik/herbert-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pczarnik/herbert-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pczarnik/herbert-base-ner") model = AutoModelForTokenClassification.from_pretrained("pczarnik/herbert-base-ner") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f8bd14518a0ad9d0cbc9bcb2646731899d39f2816d99e06c84c3a56d15831ab
- Size of remote file:
- 496 MB
- SHA256:
- 310d977a66281098775970c548b6c0cd794200036bfd58530822a0e0aada534f
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