Instructions to use andreasmadsen/efficient_mlm_m0.50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreasmadsen/efficient_mlm_m0.50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="andreasmadsen/efficient_mlm_m0.50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("andreasmadsen/efficient_mlm_m0.50") model = AutoModelForMaskedLM.from_pretrained("andreasmadsen/efficient_mlm_m0.50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from andreasmadsen/efficient_mlm_m0.50: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/andreasmadsen/efficient_mlm_m0.50/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://andreasmadsen/efficient_mlm_m0.50/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/andreasmadsen/efficient_mlm_m0.50/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 2ef7c4af2313928bf658953abdcd0e2ebc17fc86ea4e28cd4717e1af26dbc3c6
- Size of remote file:
- 1.42 GB
- SHA256:
- cd2d5a8f007a29a8c2dde11901444dd85cc4b31dd4c7621df34f5806e67cd61e
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