Added model card

README.md

@@ -1,3 +1,37 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: sentence-similarity
+---
+ONNX port of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) adjusted to return attention weights.
+
+This model is intended to be used for [BM42 searches](https://qdrant.tech/articles/bm42/).
+
+### Usage
+
+Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
+
+```py
+from fastembed import SparseTextEmbedding
+
+documents = [
+    "You should stay, study and sprint.",
+    "History can only prepare us to be surprised yet again.",
+]
+
+model = SparseTextEmbedding(model_name="Qdrant/bm42-all-minilm-l6-v2-attentions")
+embeddings = list(embedding_model.embed(documents))
+
+# [
+#     SparseEmbedding(values=array([0.26399775, 0.24662513, 0.47077307]),
+#                     indices=array([1881538586, 150760872, 1932363795])),
+#     SparseEmbedding(values=array(
+#         [0.38320042, 0.25453135, 0.18017513, 0.30432631, 0.1373556]),
+#                     indices=array([
+#                         733618285, 1849833631, 1008800696, 2090661150,
+#                         1117393019
+#                     ]))
+# ]
+
+```