Instructions to use Wanjiru/autotrain_gro_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wanjiru/autotrain_gro_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Wanjiru/autotrain_gro_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Wanjiru/autotrain_gro_ner") model = AutoModelForTokenClassification.from_pretrained("Wanjiru/autotrain_gro_ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3396209fca2ab27e0a3502317a904eb420d7da8846117c4f07b9bdf5eee81cd8
- Size of remote file:
- 1.34 GB
- SHA256:
- 54041b748617d7fbd5f0a9490a3b1615756c173a0c0f1f4e6bd5866996eb9477
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