Instructions to use andreasmadsen/efficient_mlm_m0.70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreasmadsen/efficient_mlm_m0.70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="andreasmadsen/efficient_mlm_m0.70")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("andreasmadsen/efficient_mlm_m0.70") model = AutoModelForMaskedLM.from_pretrained("andreasmadsen/efficient_mlm_m0.70", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f70ca6c05841971c4215d11fac525e47d922aec7cb76396e9d8fe19136601075
- Size of remote file:
- 1.42 GB
- SHA256:
- 198c834377f789d4529598dc7936770d555e23b051627213fff986e863754be0
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