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
Download train_state.json from MineAITechnology/mine-embed-v2: direct link, hf CLI and curl.
- Browser
- Download file 273 Bytes
-
https://huggingface.co/MineAITechnology/mine-embed-v2/resolve/main/train_state.json
- Command line
-
hf download hf://MineAITechnology/mine-embed-v2/train_state.json
-
curl -L -o train_state.json https://huggingface.co/MineAITechnology/mine-embed-v2/resolve/main/train_state.json
273 Bytes
| { | |
| "stage": 2, | |
| "elapsed": { | |
| "1": 32401.568507432938, | |
| "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 | |
| } |