Instructions to use d4data/EnviDueDiligence_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d4data/EnviDueDiligence_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="d4data/EnviDueDiligence_NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("d4data/EnviDueDiligence_NER") model = AutoModelForTokenClassification.from_pretrained("d4data/EnviDueDiligence_NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bbebe1407e423f543e84c6e756ae6c38b6ef9af136e88d8009c3e5368a236d3
- Size of remote file:
- 1.06 kB
- SHA256:
- 83b40f9793686376d734c9061f93e730570d8c850d986b48ac3127b9a7cbd3b1
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