diff --git a/docs/_src/tutorials/tutorials/2.md b/docs/_src/tutorials/tutorials/2.md index c3bc0433b..e814c430c 100644 --- a/docs/_src/tutorials/tutorials/2.md +++ b/docs/_src/tutorials/tutorials/2.md @@ -41,7 +41,7 @@ There are two ways to generate training data 1. **Annotation**: You can use the [annotation tool](https://github.com/deepset-ai/haystack#labeling-tool) to label your data, i.e. highlighting answers to your questions in a document. The tool supports structuring your workflow with organizations, projects, and users. The labels can be exported in SQuAD format that is compatible for training with Haystack. -![Snapshot of the annotation tool](https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/img/annotation_tool.png) +![Snapshot of the annotation tool](https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/_src/img/annotation_tool.png) 2. **Feedback**: For production systems, you can collect training data from direct user feedback via Haystack's [REST API interface](https://github.com/deepset-ai/haystack#rest-api). This includes a customizable user feedback API for providing feedback on the answer returned by the API. The API provides a feedback export endpoint to obtain the feedback data for fine-tuning your model further. diff --git a/docs/_src/tutorials/tutorials/6.md b/docs/_src/tutorials/tutorials/6.md index 1b5ecb3b7..6261ff08e 100644 --- a/docs/_src/tutorials/tutorials/6.md +++ b/docs/_src/tutorials/tutorials/6.md @@ -64,7 +64,7 @@ Original Code: https://fburl.com/qa-dpr Make sure you enable the GPU runtime to experience decent speed in this tutorial. **Runtime -> Change Runtime type -> Hardware accelerator -> GPU** - + ```python diff --git a/tutorials/Tutorial2_Finetune_a_model_on_your_data.ipynb b/tutorials/Tutorial2_Finetune_a_model_on_your_data.ipynb index 18e5bff8c..a698a9e61 100644 --- a/tutorials/Tutorial2_Finetune_a_model_on_your_data.ipynb +++ b/tutorials/Tutorial2_Finetune_a_model_on_your_data.ipynb @@ -55,7 +55,7 @@ "\n", "1. **Annotation**: You can use the [annotation tool](https://github.com/deepset-ai/haystack#labeling-tool) to label your data, i.e. highlighting answers to your questions in a document. The tool supports structuring your workflow with organizations, projects, and users. The labels can be exported in SQuAD format that is compatible for training with Haystack.\n", "\n", - "![Snapshot of the annotation tool](https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/img/annotation_tool.png)\n", + "![Snapshot of the annotation tool](https://raw.githubusercontent.com/deepset-ai/haystack/master/docs/_src/img/annotation_tool.png)\n", "\n", "2. **Feedback**: For production systems, you can collect training data from direct user feedback via Haystack's [REST API interface](https://github.com/deepset-ai/haystack#rest-api). This includes a customizable user feedback API for providing feedback on the answer returned by the API. The API provides a feedback export endpoint to obtain the feedback data for fine-tuning your model further.\n", "\n", diff --git a/tutorials/Tutorial6_Better_Retrieval_via_DPR.ipynb b/tutorials/Tutorial6_Better_Retrieval_via_DPR.ipynb index 9e644f5f3..0f2a4180e 100644 --- a/tutorials/Tutorial6_Better_Retrieval_via_DPR.ipynb +++ b/tutorials/Tutorial6_Better_Retrieval_via_DPR.ipynb @@ -71,7 +71,7 @@ "Make sure you enable the GPU runtime to experience decent speed in this tutorial. \n", "**Runtime -> Change Runtime type -> Hardware accelerator -> GPU**\n", "\n", - "" + "" ] }, {