|
--- |
|
license: apache-2.0 |
|
pipeline_tag: sentence-similarity |
|
base_model: |
|
- BAAI/bge-base-en-v1.5 |
|
--- |
|
|
|
Quantized ONNX port of [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) 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="BAAI/bge-base-en-v1.5") |
|
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) |
|
# ] |
|
``` |
