Update README.md

README.md

@@ -4,4 +4,28 @@ tags:
 - feature-extraction
 - embeddings
 - sentence-similarity
----
+---
+# LaBSE for French and German
+This is a shortened version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE). The model was prepaired with the direct help of [cointegrated](https://huggingface.co/cointegrated), the author of the [LaBSE-en-ru model](https://huggingface.co/cointegrated/LaBSE-en-ru).
+
+The current model includes only French and German tokens, and the vocabulary is thus 10% of the original while number of parameters in the whole model is 27% of the original.
+ 
+To get the sentence embeddings, you can  use the following code:
+```python
+import torch
+from transformers import AutoTokenizer, AutoModel
+tokenizer = AutoTokenizer.from_pretrained("EIStakovskii/LaBSE-fr-de")
+model = AutoModel.from_pretrained("EIStakovskii/LaBSE-fr-de")
+sentences = ["Wie geht es dir?", "Comment vas-tu?"]
+encoded_input = tokenizer(sentences, padding=True, truncation=True, max_length=64, return_tensors='pt')
+with torch.no_grad():
+    model_output = model(**encoded_input)
+embeddings = model_output.pooler_output
+embeddings = torch.nn.functional.normalize(embeddings)
+print(embeddings)
+```
+
+## Reference:
+Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Narveen Ari, Wei Wang. [Language-agnostic BERT Sentence Embedding](https://arxiv.org/abs/2007.01852). July 2020
+
+License: [https://tfhub.dev/google/LaBSE/1](https://tfhub.dev/google/LaBSE/1)