Instructions to use jtlicardo/bpmn-information-extraction-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jtlicardo/bpmn-information-extraction-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jtlicardo/bpmn-information-extraction-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jtlicardo/bpmn-information-extraction-v2") model = AutoModelForTokenClassification.from_pretrained("jtlicardo/bpmn-information-extraction-v2") - Notebooks
- Google Colab
- Kaggle
what are the Steps to do the same works but in other seanario
#3
by MohamedZouabi - opened
what are the Steps to do the same works but with property and real state information extraction
i want to enter an input like "i am looking for 2 bedrooms with price aound 2580 eur , in newyork" , and the model return the numbers of bedrooms , price and location ?
I think you're looking for a more general NER model, try this:
https://huggingface.co/spacy/en_core_web_lg?text=i+am+looking+for+2+bedrooms+with+price+aound+2580+euros+%2C+in+New+York
jtlicardo changed discussion status to closed