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). | |
> Note: | |
This model is supposed to be used with Qdrant. Vectors have to be configured with [Modifier.IDF](https://qdrant.tech/documentation/concepts/indexing/?q=modifier#idf-modifier). | |
```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) | |
# ] | |
``` |