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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BlackKakapo/cupidon-tiny-ro") model = AutoModel.from_pretrained("BlackKakapo/cupidon-tiny-ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from BlackKakapo/cupidon-tiny-ro: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/BlackKakapo/cupidon-tiny-ro/resolve/main/tokenizer.json
- Command line
-
hf download hf://BlackKakapo/cupidon-tiny-ro/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/BlackKakapo/cupidon-tiny-ro/resolve/main/tokenizer.json
712 kB
- Xet hash:
- ec658b372f012704bfa7dd366c2b57589afc80e04942a8ad52db56d18da0b31c
- Size of remote file:
- 712 kB
- SHA256:
- 91f1def9b9391fdabe028cd3f3fcc4efd34e5d1f08c3bf2de513ebb5911a1854
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