Create README.md

README.md

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+---
+pipeline_tag: text-classification
+license: mit
+datasets:
+- squad
+- eli5
+- sentence-transformers/embedding-training-data
+language:
+- da
+library_name: sentence-transformers
+---
+
+# MiniLM-L6-danish-reranker
+
+This is a lightweight (~22 M parameters) [sentence-transformers](https://www.SBERT.net) model for Danish NLP: It takes two sentences as input and outputs a relevance score. Therefore, the model can be used for information retrieval, e.g. given a query and candidate matches, rank the candidates by their relevance. 
+
+The maximum sequence length is 512 tokens (for both passages).
+
+The model was not pre-trained from scratch but adapted from the English version of [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2) with a [Danish tokenizer](https://huggingface.co/KennethTM/bert-base-uncased-danish).
+
+Trained on ELI5 and SQUAD data machine translated from English to Danish.
+
+## Usage with Transformers
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model = AutoModelForSequenceClassification.from_pretrained('KennethTM/MiniLM-L6-danish-reranker')
+tokenizer = AutoTokenizer.from_pretrained('KennethTM/MiniLM-L6-danish-reranker')
+features = tokenizer(['Kører der cykler på vejen?', 'Kører der cykler på vejen?'], ['En panda løber på vejen.', 'En mand kører hurtigt forbi på cykel.'],  padding=True, truncation=True, return_tensors="pt")
+
+model.eval()
+with torch.no_grad():
+    scores = model(**features).logits
+    print(scores)
+```
+
+## Usage with SentenceTransformers
+
+The usage becomes easier when you have [SentenceTransformers](https://www.sbert.net/) installed. Then, you can use the pre-trained models like this:
+```python
+from sentence_transformers import CrossEncoder
+model = CrossEncoder('KennethTM/MiniLM-L6-danish-reranker', max_length=512)
+scores = model.predict([('Kører der cykler på vejen?', 'Kører der cykler på vejen?'), ('Kører der cykler på vejen?', 'En mand kører hurtigt forbi på cykel.')])
+```