Text Classification
MLX
GLiNER
GLiNER2
English
extractor
deberta-v3
token-classification
named-entity-recognition
apple-silicon
decision-model
Instructions to use aufklarer/GLiNER2.5-Decide-340M-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use aufklarer/GLiNER2.5-Decide-340M-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download aufklarer/GLiNER2.5-Decide-340M-MLX --local-dir GLiNER2.5-Decide-340M-MLX
- GLiNER
How to use aufklarer/GLiNER2.5-Decide-340M-MLX with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("aufklarer/GLiNER2.5-Decide-340M-MLX") 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 aufklarer/GLiNER2.5-Decide-340M-MLX with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("aufklarer/GLiNER2.5-Decide-340M-MLX") # 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
- Local Apps Settings
- LM Studio
- Atomic Chat
Download export.json from aufklarer/GLiNER2.5-Decide-340M-MLX: direct link, hf CLI and curl.
- Browser
- Download file 394 Bytes
-
https://huggingface.co/aufklarer/GLiNER2.5-Decide-340M-MLX/resolve/main/export.json
- Command line
-
hf download hf://aufklarer/GLiNER2.5-Decide-340M-MLX/export.json
-
curl -L -o export.json https://huggingface.co/aufklarer/GLiNER2.5-Decide-340M-MLX/resolve/main/export.json
394 Bytes
| { | |
| "model": "fastino/GLiNER2.5-Decide", | |
| "revision": "7ee5da4c2415e32259bcdc0b1a7367c32ce8d6f6", | |
| "format": "gliner2-mlx-fp32", | |
| "weights_sha256": "463550909d8def2a009eaeca3b19628fea3c831abd99bf561d2002ecd6e96361", | |
| "weights_bytes": 1945829412, | |
| "reference_implementation": "https://github.com/Andrew-Chen-Wang/gliner2-mlx", | |
| "reference_license": "MIT", | |
| "model_license": "apache-2.0" | |
| } |