Libraries Transformers How to use dispatchAI/EmbeddingGemma-300M-mobile with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("dispatchAI/EmbeddingGemma-300M-mobile", dtype="auto") llama-cpp-python How to use dispatchAI/EmbeddingGemma-300M-mobile with llama-cpp-python:
# !pip install llama-cpp-python
from llama_cpp import Llama
llm = Llama.from_pretrained(
repo_id="dispatchAI/EmbeddingGemma-300M-mobile",
filename="model.gguf",
)
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output) Notebooks Google Colab Kaggle Local Apps Settings llama.cpp How to use dispatchAI/EmbeddingGemma-300M-mobile with llama.cpp:
Install (macOS, Linux) curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dispatchAI/EmbeddingGemma-300M-mobile
# Run inference directly in the terminal:
llama cli -hf dispatchAI/EmbeddingGemma-300M-mobile Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dispatchAI/EmbeddingGemma-300M-mobile
# Run inference directly in the terminal:
llama cli -hf dispatchAI/EmbeddingGemma-300M-mobile Use pre-built binary # Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf dispatchAI/EmbeddingGemma-300M-mobile
# Run inference directly in the terminal:
./llama-cli -hf dispatchAI/EmbeddingGemma-300M-mobile Build from source code git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf dispatchAI/EmbeddingGemma-300M-mobile
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dispatchAI/EmbeddingGemma-300M-mobile Use Docker docker model run hf.co/dispatchAI/EmbeddingGemma-300M-mobile LM Studio Jan Ollama How to use dispatchAI/EmbeddingGemma-300M-mobile with Ollama:
ollama run hf.co/dispatchAI/EmbeddingGemma-300M-mobile Unsloth Studio How to use dispatchAI/EmbeddingGemma-300M-mobile with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL) 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 dispatchAI/EmbeddingGemma-300M-mobile to start chatting Install Unsloth Studio (Windows) 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 dispatchAI/EmbeddingGemma-300M-mobile to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for dispatchAI/EmbeddingGemma-300M-mobile to start chatting Atomic Chat new Docker Model Runner How to use dispatchAI/EmbeddingGemma-300M-mobile with Docker Model Runner:
docker model run hf.co/dispatchAI/EmbeddingGemma-300M-mobile Lemonade How to use dispatchAI/EmbeddingGemma-300M-mobile with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull dispatchAI/EmbeddingGemma-300M-mobile Run and chat with the model lemonade run user.EmbeddingGemma-300M-mobile-{{QUANT_TAG}} List all available models lemonade list 
