Added time-series blogs to the models (#23857)
* added blogs to docs * removed new-line
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@@ -25,6 +25,8 @@ The abstract from the paper is the following:
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This model was contributed by [elisim](https://huggingface.co/elisim) and [kashif](https://huggingface.co/kashif).
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The original code can be found [here](https://github.com/zhouhaoyi/Informer2020).
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Tips:
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- Check out the Informer blog-post in HuggingFace blog: [Multivariate Probabilistic Time Series Forecasting with Informer](https://huggingface.co/blog/informer)
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## InformerConfig
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@@ -25,6 +25,7 @@ The Time Series Transformer model is a vanilla encoder-decoder Transformer for t
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Tips:
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- Check out the Time Series Transformer blog-post in HuggingFace blog: [Probabilistic Time Series Forecasting with 🤗 Transformers](https://huggingface.co/blog/time-series-transformers)
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- Similar to other models in the library, [`TimeSeriesTransformerModel`] is the raw Transformer without any head on top, and [`TimeSeriesTransformerForPrediction`]
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adds a distribution head on top of the former, which can be used for time-series forecasting. Note that this is a so-called probabilistic forecasting model, not a
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point forecasting model. This means that the model learns a distribution, from which one can sample. The model doesn't directly output values.
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