Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
Transformers
xlm-roberta
feature-extraction
zero-shot-classification
text-embeddings-inference
Instructions to use sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx") model = AutoModel.from_pretrained("sayed0am/sn-xlm-roberta-base-snli-mnli-anli-xnli-onnx") - Notebooks
- Google Colab
- Kaggle
| { | |
| "max_seq_length": 128, | |
| "do_lower_case": false | |
| } |