Cupidon Small Ro

🚀 cupidon-small-ro

Here comes cupidon-small-ro, a model with a small name but big ambitions. Fine - tuned from the powerful sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2, this sentence-transformers model can capture the meaning of Romanian sentences with remarkable accuracy. It is compact yet efficient, delivering a strong semantic impact. It proves that "small" can still make a big impression, especially in semantic textual similarity, search, or clustering tasks. 💔💬

📦 Installation

Using this model becomes easy when you have sentence-transformers installed. You can install it with the following command:

pip install -U sentence-transformers

💻 Usage Examples

Basic Usage (Sentence - Transformers)

If you have sentence-transformers installed, you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('BlackKakapo/cupidon-small-ro')
embeddings = model.encode(sentences)
print(embeddings)

Advanced Usage (HuggingFace Transformers)

Without sentence-transformers, you can use the model as follows. First, pass your input through the transformer model, then apply the appropriate pooling - operation on top of the contextualized word embeddings.

from transformers import AutoTokenizer, AutoModel
import torch


#Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)


# Sentences we want sentence embeddings for
sentences = ['This is an example sentence', 'Each sentence is converted']

# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('BlackKakapo/cupidon-small-ro')
model = AutoModel.from_pretrained('BlackKakapo/cupidon-small-ro')

📄 License

This dataset is licensed under Apache 2.0.

📚 Documentation

Citation

If you use BlackKakapo/cupidon-mini-ro in your research, please cite this model as follows:

@misc{cupidon-small-ro,
  title={BlackKakapo/cupidon-small-ro},
  author={BlackKakapo},
  year={2025},
}

Information Table