Sentence Similarity
sentence-transformers
Safetensors
Assamese
gemma3_text
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/embeddinggemma-asm-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/embeddinggemma-asm-16384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/embeddinggemma-asm-16384") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<eos>", | |
| "is_local": true, | |
| "mask_token": "<mask>", | |
| "model_max_length": 2048, | |
| "pad_token": "<pad>", | |
| "padding_side": "right", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>" | |
| } | |