uni2ts
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Unified Training of Universal Time Series Forecasting Transformers
In MoiraiForecast, you have implemented both `create_predictor` and `forward`. What is the difference between these two methods, and if there are differences, what scenarios should they be used in respectively?...
MultiOutSizeLinear.forward self.out_features_ls is [32, 64, 128, 256, 512] because weights_logits:4 * [8, 16, 32, 64, 256] when out_feat_size is 8, the "torch.eq(out_feat_size, feat_size).unsqueeze(-1) " is always is False then the...
Hi, Thank you for your contributions. I would like to know if the forecasts generated are interdependent. For example, if I need to forecast stock prices for 7 consecutive days,...
AttributeError: type object 'MoiraiModule' has no attribute 'from_pretrained' I'm facing this issue when trying to run the model
Hi. I'm working on enhancing long sequence forecasting performance through finetuning. I have successfully replicated the zero-shot learning results shown in Table 22 and will use them as a baseline...
Hello, I really appreciate your work as it got such a surprising performance in zero-shot setting. But I‘ve gotten a problem while fine-tuning using your command 'python -m cli.finetune run_name=example_run...
Thank you for your contributions and those of your colleagues. I am working on a multivariate time series forecasting task. My data consists of 31 time series, including 30 time...
Hi @gorold. May I clarify the setup of [the prediction mask](https://github.com/SalesforceAIResearch/uni2ts/blob/main/src/uni2ts/model/moirai/finetune.py#L452) in validation dataset in MoiraiFinetune? ``` + EvalMaskedPrediction( mask_length=-prediction_length % patch_size, # num of patches for prediction? target_field="target", truncate_fields=("variate_id",...
Hi, I wanted to fine tune the model on my own dataset however with my own custom loss. Could you give an example on how to do that? It would...
Hi, First of all thank for the great work! everything works almost plug-and-play for inference. I am having trouble while fine-tuning I usually got 2 errors: `logits: torch.Size([16, 512, 128]))...