GLiNER2
Safetensors
Chinese
English
extractor
intent-classification
slot-filling
information-extraction
home-robot
chinese
Instructions to use Icerm/gliner2-robot-multi-v11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use Icerm/gliner2-robot-multi-v11 with GLiNER2:
from gliner2 import GLiNER2 model = GLiNER2.from_pretrained("Icerm/gliner2-robot-multi-v11") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 920fad91bae09682666082a819c01b4a601ac817a9d5f9e70988c798c105f179
- Size of remote file:
- 16 MB
- SHA256:
- f6df10ec83bea993035b2dd7c39345a3d4fcf23421c2adb6cb4ffc1e6d1bc4b5
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