Instructions to use lotusbro/x5-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lotusbro/x5-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lotusbro/x5-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lotusbro/x5-ner") model = AutoModelForTokenClassification.from_pretrained("lotusbro/x5-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d83d8a8df0499e5def76897184cec4138e620fed29b653e82dd81cce9437fb24
- Size of remote file:
- 2.24 GB
- SHA256:
- 24b5453b3b6cda370823eaf2613d4b02c3b1e3f330cb89b628a43ecb7c09da92
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