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---
pipeline_tag: sentence-similarity
language: en
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- onnx
---
# ONNX convert all-roberta-large-v1
## Conversion of [sentence-transformers/all-roberta-large-v1](https://huggingface.co/sentence-transformers/all-roberta-large-v1)
## Usage (HuggingFace Optimum)
Using this model becomes easy when you have [optimum](https://github.com/huggingface/optimum) installed:
```
python -m pip install optimum
```
Then you can use the model like this:
```python
from optimum.onnxruntime.modeling_ort import ORTModelForCustomTasks
model = ORTModelForCustomTasks.from_pretrained("vamsibanda/sbert-all-roberta-large-v1-with-pooler")
tokenizer = AutoTokenizer.from_pretrained("vamsibanda/sbert-all-roberta-large-v1-with-pooler")
inputs = tokenizer("I love burritos!", return_tensors="pt")
pred = model(**inputs)
embedding = pred['pooler_output']
``` |