Update README.md

README.md

@@ -39,6 +39,37 @@ print(embeddings)
 
 ```
 
+## Usage (FastEmbed)
+
+Using this model becomes easy when you have [FastEmbed](https://github.com/qdrant/fastembed) installed:
+
+```
+pip install fastembed
+```
+
+Then you can use the model like this:
+
+```python
+from fastembed import TextEmbedding
+from fastembed.common.model_description import PoolingType, ModelSource
+
+sentences = ["Una ragazza si acconcia i capelli.", "Una ragazza si sta spazzolando i capelli."]
+
+TextEmbedding.add_custom_model(
+    model="nickprock/sentence-bert-base-italian-uncased",
+    pooling=PoolingType.MEAN,
+    normalization=True,
+    sources=ModelSource(hf="nickprock/sentence-bert-base-italian-uncased"),  # can be used with an `url` to load files from a private storage
+    dim=768,
+    model_file="onnx/model_qint8_avx512_vnni.onnx",  # can be used to load an already supported model with another optimization or quantization, e.g. onnx/model_O4.onnx
+)
+
+model = TextEmbedding(model_name="nickprock/sentence-bert-base-italian-uncased")
+embeddings = list(model.embed(sentences))
+print(embeddings)
+
+```
+
 
 
 ## Usage (HuggingFace Transformers)