Sentence Similarity
sentence-transformers
Safetensors
Chinese
English
text-embeddings-inference
feature-extraction
semantic-search
retrieval
traditional-chinese
lora
Instructions to use BluePlanetAI/BPVELA-E560M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BluePlanetAI/BPVELA-E560M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BluePlanetAI/BPVELA-E560M") sentences = [ "那是 個快樂的人", "那是 條快樂的狗", "那是 個非常幸福的人", "今天是晴天" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from BluePlanetAI/BPVELA-E560M: direct link, hf CLI and curl.
- Browser
- Download file 313 Bytes
-
https://huggingface.co/BluePlanetAI/BPVELA-E560M/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://BluePlanetAI/BPVELA-E560M/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/BluePlanetAI/BPVELA-E560M/resolve/main/1_Pooling/config.json
313 Bytes
| { | |
| "word_embedding_dimension": 1024, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |