How to use disham993/electrical-embeddinggemma-ir_lora with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("disham993/electrical-embeddinggemma-ir_lora") 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]
How to use disham993/electrical-embeddinggemma-ir_lora with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for disham993/electrical-embeddinggemma-ir_lora to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for disham993/electrical-embeddinggemma-ir_lora to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for disham993/electrical-embeddinggemma-ir_lora to start chatting
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="disham993/electrical-embeddinggemma-ir_lora", max_seq_length=2048, )
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