Instructions to use h2oai/embeddinggemma-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use h2oai/embeddinggemma-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("h2oai/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] - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
dcdf545 | 1 2 3 4 5 6 7 8 | {
"cache_implementation": "hybrid",
"do_sample": true,
"top_k": 64,
"top_p": 0.95,
"transformers_version": "4.57.0.dev0"
}
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