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 tokenizer_config.json from BluePlanetAI/BPVELA-E560M: direct link, hf CLI and curl.
- Browser
- Download file 354 Bytes
-
https://huggingface.co/BluePlanetAI/BPVELA-E560M/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://BluePlanetAI/BPVELA-E560M/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/BluePlanetAI/BPVELA-E560M/resolve/main/tokenizer_config.json
354 Bytes
| { | |
| "add_prefix_space": true, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "is_local": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |