[DOCS]: FastEmbed embedding function

docs/embeddings.md

@@ -21,6 +21,7 @@ Chroma provides lightweight wrappers around popular embedding providers, making
 | [Hugging Face Embedding Server](/embeddings/hugging-face-embedding-server) | ✅  | ✅ |
 | [Jina AI](/embeddings/jinaai) | ✅  | ✅ |
 | [Roboflow](/embeddings/roboflow-api) | ✅  | ➖ |
+| [FastEmbed](/embeddings/fastembed) | ✅  | ➖ |
 
 We welcome pull requests to add new Embedding Functions to the community.
 

docs/embeddings/fastembed.md

@@ -0,0 +1,28 @@
+---
+---
+
+# FastEmbed
+
+[FastEmbed](https://qdrant.github.io/fastembed/) is a lightweight, CPU-first Python library built for embedding generation.
+
+This embedding function requires the `fastembed` package. To install it, run
+
+```pip install fastembed```.
+
+You can find a list of all the supported models [here](https://qdrant.github.io/fastembed/examples/Supported_Models/).
+
+## Example usage:
+
+Using the default BAAI/bge-small-en-v1.5 model.
+
+```python
+from chromadb.utils.embedding_functions import FastEmbedEmbeddingFunction
+ef = FastEmbedEmbeddingFunction()
+```
+
+Additionally, you can also configure the cache directory, number of threads and other FastEmbed options.
+
+```python
+from chromadb.utils.embedding_functions import FastEmbedEmbeddingFunction
+ef = FastEmbedEmbeddingFunction(model_name="nomic-ai/nomic-embed-text-v1.5", cache_dir="models_cache", threads=5)
+```