Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
roberta
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/msmarco-roberta-base-ance-firstp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/msmarco-roberta-base-ance-firstp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/msmarco-roberta-base-ance-firstp") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Add exported openvino model 'openvino_model_qint8_quantized.xml'
Browse files
openvino/openvino_model_qint8_quantized.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ad6017d52f0e9fe33c29ef9a43ad413ac924c66247e4f0fc7bf1413b521670a7
|
| 3 |
+
size 125216836
|
openvino/openvino_model_qint8_quantized.xml
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|