use std::{rc::Rc, cell::RefCell};
We could just delete this assertion. Or we could just set the model to eval mode. Contrary to the name, it has nothing to do with whether the model is trainable or not. Eval mode just turns off train time behavior. Historically, this meant no dropout and using stored batch norm statistics rather than per-batch statistics. With modern LLM’s, this means, well, nothing—there typically are no train time specific behaviors. requires_grad controls whether gradients are tracked and only the parameters passed to the optimizer are updated.
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There is no single "right" answer on whether you should ditch WebKit (and Tauri). We have particular use cases (we are all snowflakes, right?) that make things complicated. Many apps would have close to zero problems.。业内人士推荐谷歌作为进阶阅读
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