Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
dpr
text-embeddings-inference
Instructions to use headlesstech/semantic_xlmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use headlesstech/semantic_xlmr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("headlesstech/semantic_xlmr") sentences = [ "আমি বাংলায় গান গাই", "I sing in Bangla", "I sing in Bengali", "I sing in English", "আমি গান গাই না " ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [5, 5] - Transformers
How to use headlesstech/semantic_xlmr with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("headlesstech/semantic_xlmr") model = AutoModelForMultimodalLM.from_pretrained("headlesstech/semantic_xlmr") - Notebooks
- Google Colab
- Kaggle
Ctrl+K