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@@ -17,7 +17,7 @@ Previous methods largely rely on in-context approaches to generate instructions,
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  Inspired by this, we took this approach further by grounding the generations in user-provided context passages.
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  Further, the model is trained to generate questions involving complex scenarios that require detailed reasoning, allowing for models trained on the generated data to reason step-by-step.
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- An example notebook is provided [here](https://gist.github.com/euclaise/bb7113b9596666cbf939484156375f29), which details how to load and sample from the model.
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  Alternatively, here's a minimal example:
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  ```
 
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  Inspired by this, we took this approach further by grounding the generations in user-provided context passages.
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  Further, the model is trained to generate questions involving complex scenarios that require detailed reasoning, allowing for models trained on the generated data to reason step-by-step.
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+ An example notebook is provided [here](https://huggingface.co/NousResearch/Genstruct-7B/blob/main/notebook.ipynb), which details how to load and sample from the model.
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  Alternatively, here's a minimal example:
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  ```