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README.md

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 base_model:
 - sentence-transformers/xlm-r-distilroberta-base-paraphrase-v1
 ---
+# This Model is the [cross-en-de-roberta-sentence-transformer](https://huggingface.co/T-Systems-onsite/cross-en-de-roberta-sentence-transformer) but with the missing files from the Base-Model to mitigate errors/warnings which can be problematic with some frameworks
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 # Cross English & German RoBERTa for Sentence Embeddings
 This model is intended to [compute sentence (text) embeddings](https://www.sbert.net/examples/applications/computing-embeddings/README.html) for English and German text. These embeddings can then be compared with [cosine-similarity](https://en.wikipedia.org/wiki/Cosine_similarity) to find sentences with a similar semantic meaning. For example this can be useful for [semantic textual similarity](https://www.sbert.net/docs/usage/semantic_textual_similarity.html), [semantic search](https://www.sbert.net/docs/usage/semantic_search.html), or [paraphrase mining](https://www.sbert.net/docs/usage/paraphrase_mining.html). To do this you have to use the [Sentence Transformers Python framework](https://github.com/UKPLab/sentence-transformers).