New intent classification engine - MiniLM L6v2 and MiniLM L12v2 ONNX

resources/models/all-MiniLM-L6-v2/README.md

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+---
+license: apache-2.0
+pipeline_tag: sentence-similarity
+---
+
+ONNX port of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) for text classification and similarity searches.
+
+### Usage
+
+Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed).
+
+```py
+from fastembed import TextEmbedding
+
+documents = [
+    "You should stay, study and sprint.",
+    "History can only prepare us to be surprised yet again.",
+]
+
+model = TextEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
+embeddings = list(model.embed(documents))
+
+# [
+#     array([
+#         0.00611658, 0.00068912, -0.0203846, ..., -0.01751488, -0.01174267,
+#         0.01463472
+#     ],
+#           dtype=float32),
+#     array([
+#         0.00173448, -0.00329958, 0.01557874, ..., -0.01473586, 0.0281806,
+#         -0.00448205
+#     ],
+#           dtype=float32)
+# ]
+```