Instructions to use edugp/data2vec-nlp-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edugp/data2vec-nlp-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="edugp/data2vec-nlp-base")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("edugp/data2vec-nlp-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8b9d0f8b8ee47e6b8432dda9cad7af39aff6ddf38a301935434f563c08173dc
- Size of remote file:
- 499 MB
- SHA256:
- 5ddd3b1e4f5c2d6566adc2a6b913b661d37e8854bcdeafc223b65ee85568bf84
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