Instructions to use andreasmadsen/efficient_mlm_m0.15-801010 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreasmadsen/efficient_mlm_m0.15-801010 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="andreasmadsen/efficient_mlm_m0.15-801010")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("andreasmadsen/efficient_mlm_m0.15-801010") model = AutoModelForMaskedLM.from_pretrained("andreasmadsen/efficient_mlm_m0.15-801010", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from andreasmadsen/efficient_mlm_m0.15-801010: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/andreasmadsen/efficient_mlm_m0.15-801010/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://andreasmadsen/efficient_mlm_m0.15-801010/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/andreasmadsen/efficient_mlm_m0.15-801010/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 183228cd4456bd9498e5b2d210815459c083898298b0fc9668836ff69f23acd1
- Size of remote file:
- 1.42 GB
- SHA256:
- 34867fd9abff0b067351208ddb61722c2d1a46231f5760d3ae3d09c5e40e7bec
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