⚡️ What is FastEmbed?
FastEmbed is an easy to use -- lightweight, fast, Python library built for retrieval augmented generation. The default embedding supports "query" and "passage" prefixes for the input text.
-
Light
- Quantized model weights
- ONNX Runtime for inference
- No hidden dependencies on PyTorch or TensorFlow via Huggingface Transformers
-
Accuracy/Recall
- Better than OpenAI Ada-002
- Default is Flag Embedding, which is top of the MTEB leaderboard
-
Fast
- About 2x faster than Huggingface (PyTorch) transformers on single queries
- Lot faster for batches!
- ONNX Runtime allows you to use dedicated runtimes for even higher throughput and lower latency
🚀 Installation
To install the FastEmbed library, pip works:
pip install fastembed
📖 Usage
from fastembed.embedding import FlagEmbedding as Embedding
documents: List[str] = [
"passage: Hello, World!",
"query: Hello, World!", # these are two different embedding
"passage: This is an example passage.",
# You can leave out the prefix but it's recommended
"fastembed is supported by and maintained by Qdrant."
]
embedding_model = Embedding(model_name="BAAI/bge-base-en", max_length=512)
embeddings: List[np.ndarray] = list(embedding_model.embed(documents))
🚒 Under the hood
Why fast?
It's important we justify the "fast" in FastEmbed. FastEmbed is fast because:
- Quantized model weights
- ONNX Runtime which allows for inference on CPU, GPU, and other dedicated runtimes
Why light?
- No hidden dependencies on PyTorch or TensorFlow via Huggingface Transformers
Why accurate?
- Better than OpenAI Ada-002
- Top of the Embedding leaderboards e.g. MTEB
Release files for fastembed 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fastembed-0.0.4.tar.gz | 9.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fastembed-0.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:19.2 kB
Release files / fastembed-0.0.4.tar.gz
| Download URL | fastembed-0.0.4.tar.gz |
|---|---|
| Size | 9.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.5.1 CPython/3.10.9 Darwin/22.5.0
|
Release files / fastembed-0.0.4-py3-none-any.whl
| Download URL | fastembed-0.0.4-py3-none-any.whl |
|---|---|
| Size | 9.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.5.1 CPython/3.10.9 Darwin/22.5.0
|
