Instructions to use Llamacha/ner_quechua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Llamacha/ner_quechua with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Llamacha/ner_quechua")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Llamacha/ner_quechua") model = AutoModelForTokenClassification.from_pretrained("Llamacha/ner_quechua") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1b19e05fe2bd2a5d23c7f9e858bf849c8bc716f091bbff9b506ff2fba6df569
- Size of remote file:
- 2.99 kB
- SHA256:
- 4cc44b6fab31ba221b7b4a02f56e29ddd984e290291c90cb508cd9706aef5f32
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