Create README

README.md

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+# CodeColBERT
+
+This model serves as the base for our semantic code retrieval system SELMA. It can be applied for indexing and retrieval using the Pyterrier bindings for ColBERT.
+
+## Training Details
+This model was trained for code retrieval. As a base, CodeBERT is used. It is trained using the official ColBERTv2 code 
+([Github](https://github.com/stanford-futuredata/ColBERT)). 
+
+Our data source is the [CodeSearchNet Challenge](https://github.com/github/CodeSearchNet).
+Training ColBERT requires a tripes of queries, positive examples and negative examples. As queries, we used the documentation 
+provided for each sample in the CodeSearchNet data set, while its code snippet serves as the positive example. Negative examples were 
+sampled randomly from the corpus. In total, we train for 400.000 steps.