Sentence Similarity
sentence-transformers
Safetensors
English
grt
geometric-rotation-transformer
feature-extraction
circular-pooling
rotational
qwen3
Instructions to use MatterWaveAI/grt-30m-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MatterWaveAI/grt-30m-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MatterWaveAI/grt-30m-embedding") 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 config_sentence_transformers.json from MatterWaveAI/grt-30m-embedding: direct link, hf CLI and curl.
- Browser
- Download file 267 Bytes
-
https://huggingface.co/MatterWaveAI/grt-30m-embedding/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://MatterWaveAI/grt-30m-embedding/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/MatterWaveAI/grt-30m-embedding/resolve/main/config_sentence_transformers.json
267 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "5.2.0.dev0", | |
| "transformers": "5.21.0.dev0", | |
| "pytorch": "2.12.0+xpu" | |
| }, | |
| "prompts": { | |
| "query": "", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } | |