ONNX convert all-MiniLM-L6-v2
Conversion of sentence-transformers/all-MiniLM-L6-v2
This is a sentence-transformers ONNX model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. This custom model takes last_hidden_state
and pooler_output
whereas the sentence-transformers exported with default ONNX config only contains last_hidden_state
as output.
Usage (HuggingFace Optimum)
Using this model becomes easy when you have optimum installed:
python -m pip install optimum
Then you can use the model like this:
from optimum.onnxruntime.modeling_ort import ORTModelForCustomTasks
model = ORTModelForCustomTasks.from_pretrained("vamsibanda/sbert-all-MiniLM-L6-with-pooler")
tokenizer = AutoTokenizer.from_pretrained("vamsibanda/sbert-all-MiniLM-L6-with-pooler")
inputs = tokenizer("I love burritos!", return_tensors="pt")
pred = model(**inputs)
embedding = pred['pooler_output']
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.