Instructions to use google/gemma-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use google/gemma-2b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="google/gemma-2b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained("google/gemma-2b")

llama-cpp-python

How to use google/gemma-2b with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="google/gemma-2b",
	filename="gemma-2b.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Inference
Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use google/gemma-2b with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf google/gemma-2b
# Run inference directly in the terminal:
llama-cli -hf google/gemma-2b

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf google/gemma-2b
# Run inference directly in the terminal:
llama-cli -hf google/gemma-2b

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 google/gemma-2b
# Run inference directly in the terminal:
./llama-cli -hf google/gemma-2b

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 google/gemma-2b
# Run inference directly in the terminal:
./build/bin/llama-cli -hf google/gemma-2b

Use Docker

docker model run hf.co/google/gemma-2b

LM Studio
Jan

vLLM

How to use google/gemma-2b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "google/gemma-2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "google/gemma-2b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/google/gemma-2b

SGLang

How to use google/gemma-2b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "google/gemma-2b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "google/gemma-2b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "google/gemma-2b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "google/gemma-2b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use google/gemma-2b with Ollama:
```
ollama run hf.co/google/gemma-2b
```

Unsloth Studio new

How to use google/gemma-2b 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 google/gemma-2b 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 google/gemma-2b to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for google/gemma-2b to start chatting

Docker Model Runner
How to use google/gemma-2b with Docker Model Runner:
```
docker model run hf.co/google/gemma-2b
```

Lemonade

How to use google/gemma-2b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull google/gemma-2b

Run and chat with the model

lemonade run user.gemma-2b-{{QUANT_TAG}}

List all available models

lemonade list

gemma 2b inference Endpoints error

#46

by gawon16 - opened Apr 9, 2024

Discussion

gawon16

Apr 9, 2024

My Inference endpoint is unable to start, I’m getting this error:

Endpoint encountered an error.
You can try restarting it using the "pause" button above. Check logs for more details.
Server message:Endpoint failed to start.

What can I do to get this running? I repeat to pause and initialize, but got a same error.

Help anyone?

osanseviero

Google org Apr 9, 2024

Hi there. Which error did you get in the logs?

gawon16

Apr 11, 2024

Hi there. Which error did you get in the logs?

2024/04/11 16:23:09 ~ {"timestamp":"2024-04-11T07:23:09.599170Z","level":"INFO","fields":{"message":"Args { model_id: "/repository", revision: None, validation_workers: 2, sharded: None, num_shard: None, quantize: None, speculate: None, dtype: None, trust_remote_code: false, max_concurrent_requests: 128, max_best_of: 2, max_stop_sequences: 4, max_top_n_tokens: 5, max_input_length: 1024, max_total_tokens: 1512, waiting_served_ratio: 1.2, max_batch_prefill_tokens: 2048, max_batch_total_tokens: None, max_waiting_tokens: 20, max_batch_size: None, cuda_graphs: [1, 2, 4, 8, 16, 32, 64, 96, 128], hostname: "r-hwgi-gemma-2b-efr-2db7c6ju-02fac-sw7e3", port: 80, shard_uds_path: "/tmp/text-generation-server", master_addr: "localhost", master_port: 29500, huggingface_hub_cache: Some("/data"), weights_cache_override: None, disable_custom_kernels: false, cuda_memory_fraction: 1.0, rope_scaling: None, rope_factor: None, json_output: true, otlp_endpoint: None, cors_allow_origin: [], watermark_gamma: None, watermark_delta: None, ngrok: false, ngrok_authtoken: None, ngrok_edge: None, tokenizer_config_path: None, disable_grammar_support: false, env: false }"},"target":"text_generation_launcher"}
2024/04/11 16:23:09 ~ {"timestamp":"2024-04-11T07:23:09.599219Z","level":"INFO","fields":{"message":"Sharding model on 4 processes"},"target":"text_generation_launcher"}
2024/04/11 16:23:09 ~ {"timestamp":"2024-04-11T07:23:09.599305Z","level":"INFO","fields":{"message":"Starting download process."},"target":"text_generation_launcher","span":{"name":"download"},"spans":[{"name":"download"}]}
2024/04/11 16:23:11 ~ {"timestamp":"2024-04-11T07:23:11.917102Z","level":"INFO","fields":{"message":"Files are already present on the host. Skipping download.\n"},"target":"text_generation_launcher"}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.402047Z","level":"INFO","fields":{"message":"Successfully downloaded weights."},"target":"text_generation_launcher","span":{"name":"download"},"spans":[{"name":"download"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.402305Z","level":"INFO","fields":{"message":"Starting shard"},"target":"text_generation_launcher","span":{"rank":1,"name":"shard-manager"},"spans":[{"rank":1,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.402306Z","level":"INFO","fields":{"message":"Starting shard"},"target":"text_generation_launcher","span":{"rank":0,"name":"shard-manager"},"spans":[{"rank":0,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.402394Z","level":"INFO","fields":{"message":"Starting shard"},"target":"text_generation_launcher","span":{"rank":2,"name":"shard-manager"},"spans":[{"rank":2,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.402847Z","level":"INFO","fields":{"message":"Starting shard"},"target":"text_generation_launcher","span":{"rank":3,"name":"shard-manager"},"spans":[{"rank":3,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.502431Z","level":"INFO","fields":{"message":"Shutting down shards"},"target":"text_generation_launcher"}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.507161Z","level":"INFO","fields":{"message":"Shard terminated"},"target":"text_generation_launcher","span":{"rank":0,"name":"shard-manager"},"spans":[{"rank":0,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.507365Z","level":"INFO","fields":{"message":"Shard terminated"},"target":"text_generation_launcher","span":{"rank":1,"name":"shard-manager"},"spans":[{"rank":1,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.507543Z","level":"INFO","fields":{"message":"Shard terminated"},"target":"text_generation_launcher","span":{"rank":2,"name":"shard-manager"},"spans":[{"rank":2,"name":"shard-manager"}]}
2024/04/11 16:23:12 ~ {"timestamp":"2024-04-11T07:23:12.507608Z","level":"INFO","fields":{"message":"Shard terminated"},"target":"text_generation_launcher","span":{"rank":3,"name":"shard-manager"},"spans":[{"rank":3,"name":"shard-manager"}]}

Here you are.

michellehbn

Apr 12, 2024

Hi @gawon16 , Thanks for reporting. We recommend updating the task in your endpoint from Question-Answering to Text-Generation. If you continue to run into an issue deploying or have further questions, please email us at api-enterprise@huggingface.co and we'll take a deeper look. Thanks again!

Renu11

Google org Aug 13, 2024

@gawon16 , I hope the issue has been resolved. Please let us know if any further assistance is needed. Thanks!

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment