Sentence Similarity
sentence-transformers
ONNX
Safetensors
OpenVINO
Transformers
Romanian
bert
feature-extraction
text-embeddings-inference
Instructions to use BlackKakapo/cupidon-tiny-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BlackKakapo/cupidon-tiny-ro with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BlackKakapo/cupidon-tiny-ro") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use BlackKakapo/cupidon-tiny-ro with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BlackKakapo/cupidon-tiny-ro") model = AutoModel.from_pretrained("BlackKakapo/cupidon-tiny-ro") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -71,7 +71,7 @@ This dataset is licensed under **Apache 2.0**.
|
|
| 71 |
## Citation
|
| 72 |
If you use BlackKakapo/cupidon-tiny-ro in your research, please cite this model as follows:
|
| 73 |
```
|
| 74 |
-
@misc{
|
| 75 |
title={BlackKakapo/cupidon-tiny-ro},
|
| 76 |
author={BlackKakapo},
|
| 77 |
year={2025},
|
|
|
|
| 71 |
## Citation
|
| 72 |
If you use BlackKakapo/cupidon-tiny-ro in your research, please cite this model as follows:
|
| 73 |
```
|
| 74 |
+
@misc{cupidon-tiny-ro,
|
| 75 |
title={BlackKakapo/cupidon-tiny-ro},
|
| 76 |
author={BlackKakapo},
|
| 77 |
year={2025},
|