Instructions to use smshahbaj/embeddinggemma-2-ecommerce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use smshahbaj/embeddinggemma-2-ecommerce with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("smshahbaj/embeddinggemma-2-ecommerce")

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
Local Apps Settings

llama.cpp

How to use smshahbaj/embeddinggemma-2-ecommerce with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible embeddings server:
llama serve -hf smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M --embeddings

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible embeddings server:
llama serve -hf smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M --embeddings

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible embeddings server:
./build/bin/llama serve -hf smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M --embeddings

Llama new
LM Studio
Jan
Ollama
How to use smshahbaj/embeddinggemma-2-ecommerce with Ollama:
```
ollama run hf.co/smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use smshahbaj/embeddinggemma-2-ecommerce with Docker Model Runner:
```
docker model run hf.co/smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M
```

Lemonade

How to use smshahbaj/embeddinggemma-2-ecommerce with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull smshahbaj/embeddinggemma-2-ecommerce:Q4_K_M

Run and chat with the model

lemonade run user.embeddinggemma-2-ecommerce-Q4_K_M

List all available models

lemonade list

Atomic Chat

embeddinggemma-2-ecommerce / 2_Normalize /config.json

smshahbaj

embeddinggemma-2-ecommerce: fine-tuned on Amazon ESCI

cfda0b0 verified 20 days ago

Download 2_Normalize/config.json from smshahbaj/embeddinggemma-2-ecommerce: direct link, hf CLI and curl.

Browser
Download file 97 Bytes

https://huggingface.co/smshahbaj/embeddinggemma-2-ecommerce/resolve/main/2_Normalize/config.json

Command line

hf download hf://smshahbaj/embeddinggemma-2-ecommerce/2_Normalize/config.json

curl -L -o config.json https://huggingface.co/smshahbaj/embeddinggemma-2-ecommerce/resolve/main/2_Normalize/config.json

Raw History Blame Contribute Delete

97 Bytes

{
    "module_input_name": "sentence_embedding",
    "module_output_name": "sentence_embedding"
}

	{
	"module_input_name": "sentence_embedding",
	"module_output_name": "sentence_embedding"
	}