Naruto LLM
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All about Narutoverse: Text-based LLM, Vision LLM, Reasoning LLM • 1 item • Updated
How to use SteveTran/naruto-gemma-2-9b with Adapters:
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("undefined")
model.load_adapter("SteveTran/naruto-gemma-2-9b", set_active=True)How to use SteveTran/naruto-gemma-2-9b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="SteveTran/naruto-gemma-2-9b", filename="Q8.gguf", )
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "What is the capital of France?"
}
]
)How to use SteveTran/naruto-gemma-2-9b with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: llama-cli -hf SteveTran/naruto-gemma-2-9b
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: llama-cli -hf SteveTran/naruto-gemma-2-9b
# 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 SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: ./llama-cli -hf SteveTran/naruto-gemma-2-9b
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 SteveTran/naruto-gemma-2-9b # Run inference directly in the terminal: ./build/bin/llama-cli -hf SteveTran/naruto-gemma-2-9b
docker model run hf.co/SteveTran/naruto-gemma-2-9b
How to use SteveTran/naruto-gemma-2-9b with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SteveTran/naruto-gemma-2-9b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "SteveTran/naruto-gemma-2-9b",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/SteveTran/naruto-gemma-2-9b
How to use SteveTran/naruto-gemma-2-9b with Ollama:
ollama run hf.co/SteveTran/naruto-gemma-2-9b
How to use SteveTran/naruto-gemma-2-9b 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 SteveTran/naruto-gemma-2-9b 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 SteveTran/naruto-gemma-2-9b to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for SteveTran/naruto-gemma-2-9b to start chatting
How to use SteveTran/naruto-gemma-2-9b with Docker Model Runner:
docker model run hf.co/SteveTran/naruto-gemma-2-9b
How to use SteveTran/naruto-gemma-2-9b with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SteveTran/naruto-gemma-2-9b
lemonade run user.naruto-gemma-2-9b-{{QUANT_TAG}}lemonade list
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "What is the capital of France?"
}
]
)We're not able to determine the quantization variants.
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="SteveTran/naruto-gemma-2-9b", filename="Q8.gguf", )