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Web demo The demo/ folder has a simple one page React app which shows how to run mask prediction with the exported ONNX model in a web browser with multithreading. Please see demo/README.md for more details. Model Checkpoints Three model versions of the model are available with different backbone sizes.
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Inference Different models require different model-parallel (MP) values: Model MP 7B 1 13B 2 70B 8 All models support sequence length up to 4096 tokens, but we pre-allocate the cache according to max_seq_len and max_batch_size values.
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--character CHARACTER The name of the character to load in chat mode by default.
--model MODEL Name of the model to load by default.
--lora LORA [LORA ...] The list of LoRAs to load.
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The human only needs to put error bars on their own forecast, not on the internal workings of the model. gh02t 1y > This sounds like it's approaching some sort of model mysticism. Models don't make forecasts, humans do. By forecasts I only mean output of a model, I've been wrapped up in time series methods where that's the usual term for model outputs.
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