Downloads · 30 days
8
1% of all-time downloads
sbert-all-roberta-large-v1-with-pooler
vamsibanda/sbert-all-roberta-large-v1-with-pooler
sbert-all-roberta-large-v1-with-pooler is a sentence similarity model from vamsibanda. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as apache-2.0.
Using this model becomes easy when you have optimum installed:
All-time downloads
1.4K
Public
Repo size
3.5 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.onnx1.4 GB · 100%
At a glance
- Task
- Sentence Similarity
- Library
- sentence-transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Jul 19, 2022
- Updated
- Sep 13, 2022
- SHA
- f788f369
Model card
From the Hugging Face model README
ONNX convert all-roberta-large-v1
Conversion of sentence-transformers/all-roberta-large-v1
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-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']
- Task
- Sentence Similarity
- Library
- sentence-transformers
- Type
- roberta
- License
- apache-2.0
- Languages
- en
- Created
- Jul 19, 2022
- Updated
- Sep 13, 2022