Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings-inference
Instructions to use noname002/embeddinggemma-300m-greennode-5fre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use noname002/embeddinggemma-300m-greennode-5fre with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("noname002/embeddinggemma-300m-greennode-5fre") 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
File size: 229 Bytes
617ccfa | 1 2 3 4 5 6 7 8 | {
"in_features": 768,
"out_features": 3072,
"bias": false,
"activation_function": "torch.nn.modules.linear.Identity",
"module_input_name": "sentence_embedding",
"module_output_name": "sentence_embedding"
} |