Sentence Similarity
sentence-transformers
ONNX
Vietnamese
English
e5
vietnamese
fp32
retrieval
document-search
Instructions to use welcomyou/e5-small-vn-archive-mix50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use welcomyou/e5-small-vn-archive-mix50 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("welcomyou/e5-small-vn-archive-mix50") 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] - Notebooks
- Google Colab
- Kaggle
| { | |
| "source_model_dir": "outputs/e5-small-mix50-v2/best", | |
| "onnx_path": "outputs/e5-small-mix50-v2-onnx-fp32/model.onnx", | |
| "pooling": "mean", | |
| "normalize": true, | |
| "opset": 17, | |
| "embedding_dim": 384, | |
| "parity_cosine_min": 0.9999998807907104, | |
| "parity_cosine_mean": 0.9999999403953552, | |
| "parity_max_abs_diff": 1.4202669262886047e-07 | |
| } |