If you find MiniLM useful in your research, please cite the following paper:
@misc{wang2020minilm,
title={MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers},
author={Wenhui Wang and Furu Wei and Li Dong and Hangbo Bao and Nan Yang and Ming Zhou},
year={2020},
eprint={2002.10957},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Runs of microsoft MiniLM-L12-H384-uncased on huggingface.co
35.0K
Total runs
0
24-hour runs
469
3-day runs
-1.3K
7-day runs
5.2K
30-day runs
More Information About MiniLM-L12-H384-uncased huggingface.co Model
MiniLM-L12-H384-uncased huggingface.co is an AI model on huggingface.co that provides MiniLM-L12-H384-uncased's model effect (), which can be used instantly with this microsoft MiniLM-L12-H384-uncased model. huggingface.co supports a free trial of the MiniLM-L12-H384-uncased model, and also provides paid use of the MiniLM-L12-H384-uncased. Support call MiniLM-L12-H384-uncased model through api, including Node.js, Python, http.
MiniLM-L12-H384-uncased huggingface.co is an online trial and call api platform, which integrates MiniLM-L12-H384-uncased's modeling effects, including api services, and provides a free online trial of MiniLM-L12-H384-uncased, you can try MiniLM-L12-H384-uncased online for free by clicking the link below.
microsoft MiniLM-L12-H384-uncased online free url in huggingface.co:
MiniLM-L12-H384-uncased is an open source model from GitHub that offers a free installation service, and any user can find MiniLM-L12-H384-uncased on GitHub to install. At the same time, huggingface.co provides the effect of MiniLM-L12-H384-uncased install, users can directly use MiniLM-L12-H384-uncased installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
MiniLM-L12-H384-uncased install url in huggingface.co: