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license: mit |
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# Model Card for sparsing-law-0.1b-relu |
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- **Paper [optional]:** [paper](todo) |
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- **Repository and demo code:** [github](https://github.com/thunlp/SparsingLaw) |
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This model is ReLU-activated and contains approximately 0.1 billion non-embedding parameters. |
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The model was trained from scratch using the pre-training dataset described in our paper, with the WSD (Warmup-Stable-Decay) learning rate scheduler. It represents the final checkpoint of the stable stage in WSD, meaning it has not undergone the decay stage. |
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