Instructions to use AK/ak_nlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AK/ak_nlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AK/ak_nlp")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AK/ak_nlp") model = AutoModelForMaskedLM.from_pretrained("AK/ak_nlp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b671fc9da36fd981f3be9d18724158cf60d9d6c46b9dae014506eddedb63274
- Size of remote file:
- 334 MB
- SHA256:
- 7d2c6427a4cb3e4add821794c3d98b9444e9128e209e99e07a04d6be0b403815
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