Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
text-embeddings
mteb
text-embeddings-inference
Instructions to use MineAITechnology/mine-embed-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MineAITechnology/mine-embed-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MineAITechnology/mine-embed-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 273 Bytes
9872ce3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"stage": 2,
"elapsed": {
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"2": 5401.360342264175
},
"step": {
"1": 3112,
"2": 806
},
"scale": 8192.0,
"sessions": 1,
"done_stages": [
1,
2
],
"finished": true,
"backbone": "google/bert_uncased_L-12_H-512_A-8",
"good": 253
} |