Token Classification
ONNX
GLiNER2
English
onnxruntime
ner
transaction-extraction
sms-parsing
deberta
on-device
mobile
Instructions to use Sowrabhm/fintext-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use Sowrabhm/fintext-extractor with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("Sowrabhm/fintext-extractor") # 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 tokenizer_extraction/spm.model from Sowrabhm/fintext-extractor: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/Sowrabhm/fintext-extractor/resolve/main/tokenizer_extraction/spm.model
- Command line
-
hf download hf://Sowrabhm/fintext-extractor/tokenizer_extraction/spm.model
-
curl -L -o spm.model https://huggingface.co/Sowrabhm/fintext-extractor/resolve/main/tokenizer_extraction/spm.model
2.46 MB
- Xet hash:
- 6bd079d8585fbcdbf47cb3a534f888b5aaa32b8994301f5c47573e6cf825d7da
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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