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@@ -73,14 +73,11 @@ Inference code is available on [GitHub](https://github.com/DataDog/toto).
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  ### Installation
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  ```bash
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- # Clone the repository
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- git clone https://github.com/DataDog/toto.git
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- cd toto
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-
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- # Install dependencies
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- pip install -r requirements.txt
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  ```
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  ### 🚀 Inference Example
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  Here's how to quickly generate forecasts using Toto:
@@ -133,9 +130,6 @@ upper_quantile = forecast.quantile(0.9)
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  For detailed inference instructions, refer to the [inference tutorial notebook](https://github.com/DataDog/toto/blob/main/toto/notebooks/inference_tutorial.ipynb).
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- ### Performance Recommendations
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- - ### **For optimal speed and reduced memory usage, install [xFormers](https://github.com/facebookresearch/xformers) and [flash-attention](https://github.com/Dao-AILab/flash-attention). Then, set `use_memory_efficient` to `True`.**
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-
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  ---
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  ### 💾 Available Checkpoints
 
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  ### Installation
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  ```bash
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+ pip install toto-ts
 
 
 
 
 
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  ```
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+ For optimal speed and reduced memory usage, you should also install [xFormers](https://github.com/facebookresearch/xformers) and [flash-attention](https://github.com/Dao-AILab/flash-attention)
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+
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  ### 🚀 Inference Example
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  Here's how to quickly generate forecasts using Toto:
 
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  For detailed inference instructions, refer to the [inference tutorial notebook](https://github.com/DataDog/toto/blob/main/toto/notebooks/inference_tutorial.ipynb).
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  ---
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  ### 💾 Available Checkpoints