How to use luokelabs/embeddinggemma-2-bf16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="luokelabs/embeddinggemma-2-bf16")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("luokelabs/embeddinggemma-2-bf16") model = AutoModel.from_pretrained("luokelabs/embeddinggemma-2-bf16", device_map="auto")
How to use luokelabs/embeddinggemma-2-bf16 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("luokelabs/embeddinggemma-2-bf16") 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]
https://huggingface.co/luokelabs/embeddinggemma-2-bf16/resolve/main/1_Pooling/config.json
hf download hf://luokelabs/embeddinggemma-2-bf16/1_Pooling/config.json
curl -L -o config.json https://huggingface.co/luokelabs/embeddinggemma-2-bf16/resolve/main/1_Pooling/config.json
