Instructions to use hivetrace/gliner-guard-uniencoder-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use hivetrace/gliner-guard-uniencoder-onnx with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("hivetrace/gliner-guard-uniencoder-onnx") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - GLiNER2
How to use hivetrace/gliner-guard-uniencoder-onnx with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("hivetrace/gliner-guard-uniencoder-onnx") # 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
Download config.json from hivetrace/gliner-guard-uniencoder-onnx: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/hivetrace/gliner-guard-uniencoder-onnx/resolve/main/config.json
- Command line
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hf download hf://hivetrace/gliner-guard-uniencoder-onnx/config.json
-
curl -L -o config.json https://huggingface.co/hivetrace/gliner-guard-uniencoder-onnx/resolve/main/config.json
48 Bytes
| { | |
| "hidden_size": 384, | |
| "vocab_size": 256000 | |
| } |