Instructions to use Llamacha/pos_quechua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Llamacha/pos_quechua with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Llamacha/pos_quechua")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Llamacha/pos_quechua") model = AutoModelForTokenClassification.from_pretrained("Llamacha/pos_quechua", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e58f6c25d011166895c9483b65aa5194e59ddf700a76649e5cd8cdbace454364
- Size of remote file:
- 3.18 kB
- SHA256:
- 504e772e593fdeb7edc0dbf898fba9d93e548bd88e868f8681739ff74df1d83b
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