Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
text-embeddings-inference
Eval Results
Instructions to use google/embeddinggemma-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use google/embeddinggemma-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("google/embeddinggemma-300m") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Format conversion onnx, rknn
#12
by litterbearjiujiu - opened
讨论能否转换格式到rk3588,rk3568等嵌入式板端npu上运行加快推理速度
有大佬尝试转换并运行成功吗
Hi @litterbearjiujiu ,
Welcome to Gemma models, you could able to find the ONNX model under the following URL from ONNX community. Please let me know if any additional assistance is required.
To know more about google/embeddinggemma-300m please visit the following ref.
Thanks.
Hi @BalakrishnaCh ! Is there a onnx conversion script ? Can I see it, please ? I'm trying to convert a fine-tuned version and none of these methods work for me: sentence-transformers (pip latest), torch.onnx.export (2.9), optimum-onnx (git), transformers (git, embeddinggemma branch). I would really appreciate some help. Thanks in advance!