Instructions to use andreasmadsen/efficient_mlm_m0.15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreasmadsen/efficient_mlm_m0.15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="andreasmadsen/efficient_mlm_m0.15")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("andreasmadsen/efficient_mlm_m0.15") model = AutoModelForMaskedLM.from_pretrained("andreasmadsen/efficient_mlm_m0.15") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc7bd52bb47c7d4093a777ab1e908fb9c253a6153f48344b75f9611b6b4589b2
- Size of remote file:
- 1.42 GB
- SHA256:
- 0622ea86e1f596b0af25de781505b4d59f9f12b78806e12ffcdb06af1bb65a4b
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