Sentence Similarity
sentence-transformers
OpenVINO
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use optimum-intel-internal-testing/stsb-bert-tiny-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use optimum-intel-internal-testing/stsb-bert-tiny-openvino with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("optimum-intel-internal-testing/stsb-bert-tiny-openvino") 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] - Transformers
How to use optimum-intel-internal-testing/stsb-bert-tiny-openvino with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("optimum-intel-internal-testing/stsb-bert-tiny-openvino") model = AutoModel.from_pretrained("optimum-intel-internal-testing/stsb-bert-tiny-openvino", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download export.json from optimum-intel-internal-testing/stsb-bert-tiny-openvino: direct link, hf CLI and curl.
- Browser
- Download file 1.23 kB
-
https://huggingface.co/optimum-intel-internal-testing/stsb-bert-tiny-openvino/resolve/main/export.json
- Command line
-
hf download hf://optimum-intel-internal-testing/stsb-bert-tiny-openvino/export.json
-
curl -L -o export.json https://huggingface.co/optimum-intel-internal-testing/stsb-bert-tiny-openvino/resolve/main/export.json
1.23 kB
| { | |
| "schema_version": 1, | |
| "export_format": "openvino", | |
| "components": { | |
| "model": { | |
| "file": "openvino_model.xml", | |
| "metadata": { | |
| "schema_version": 1, | |
| "architecture": "_ExportableModel", | |
| "packages": { | |
| "transformers": "5.19.0.dev0", | |
| "torch": "2.13.0", | |
| "openvino": "2026.4.1" | |
| }, | |
| "dtype": "float32", | |
| "device": "cpu", | |
| "kwargs": { | |
| "input_ids": { | |
| "rank": 2, | |
| "shape": [ | |
| 2, | |
| 16 | |
| ], | |
| "dtype": "int64" | |
| }, | |
| "token_type_ids": { | |
| "rank": 2, | |
| "shape": [ | |
| 2, | |
| 16 | |
| ], | |
| "dtype": "int64" | |
| }, | |
| "attention_mask": { | |
| "rank": 2, | |
| "shape": [ | |
| 2, | |
| 16 | |
| ], | |
| "dtype": "int64" | |
| } | |
| }, | |
| "input_names": [ | |
| "input_ids", | |
| "token_type_ids", | |
| "attention_mask" | |
| ], | |
| "constant_inputs": {}, | |
| "output_names": [ | |
| "token_embeddings", | |
| "sentence_embedding" | |
| ], | |
| "num_user_outputs": 2 | |
| } | |
| } | |
| } | |
| } | |