Update README.md

README.md

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 # Cross-lingual Product Matching using Transformers
+
+# Project Goal
+**Can matching knowledge be transferred between languages?**
+
+- Can we augment performance on languages with small amounts of training data by adding data from more readily available languages (English)? (E.g. Fine-tune model for the task using english data **/** Further fine-tune using few examples of target language (few-shot learning))
+- Can we achieve good performance without any data from the target language? (Zero-shot performance)
+- If it works well, how can we explain it?
+
+# Setup
+**Use this Repository**
+
+*Before installing, make sure to have [Microsoft Build Tools for C++](https://visualstudio.microsoft.com/de/visual-cpp-build-tools/)  installed for fastText*
+````bash
+cd path/to/repo
+conda env create -f environment.yml
+conda activate team_project
+````
+**Colab**
+
+- To use GitHub-Repos in Colab, when opening new notebooks, you have to -> check the box for "include private repositories" ("private Repositories einschließen" in German). Then, Colab has to be given the necessary access rights to one's GitHub-Account (via a popup).
+- To push changes: in a notebook -> Datei -> "Kopie in GitHub speichern" -> write useful commit message.
+
+**Data**
+- Datasets can be downloaded from