Sentence Similarity
sentence-transformers
PyTorch
Transformers
Hungarian
bert
feature-extraction
text-embeddings-inference
Instructions to use danieleff/hubert-base-cc-sentence-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danieleff/hubert-base-cc-sentence-transformer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danieleff/hubert-base-cc-sentence-transformer") 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 danieleff/hubert-base-cc-sentence-transformer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("danieleff/hubert-base-cc-sentence-transformer") model = AutoModel.from_pretrained("danieleff/hubert-base-cc-sentence-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 122 Bytes
15eec04 | 1 2 3 4 5 6 7 | {
"__version__": {
"sentence_transformers": "2.2.2",
"transformers": "4.26.0",
"pytorch": "1.13.1+cpu"
}
} |