Instructions to use prxshetty/gemma-3-finance-mix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prxshetty/gemma-3-finance-mix with Transformers:

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

pipe = pipeline("text-generation", model="prxshetty/gemma-3-finance-mix")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("prxshetty/gemma-3-finance-mix", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use prxshetty/gemma-3-finance-mix with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prxshetty/gemma-3-finance-mix"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prxshetty/gemma-3-finance-mix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/prxshetty/gemma-3-finance-mix

SGLang

How to use prxshetty/gemma-3-finance-mix 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 "prxshetty/gemma-3-finance-mix" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prxshetty/gemma-3-finance-mix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "prxshetty/gemma-3-finance-mix" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prxshetty/gemma-3-finance-mix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use prxshetty/gemma-3-finance-mix with Docker Model Runner:
```
docker model run hf.co/prxshetty/gemma-3-finance-mix
```

prxshetty commited on Sep 2, 2025

Commit

b1251c0

verified ·

1 Parent(s): c847f2b

Update README.md

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -21,7 +21,7 @@ language:
 # Gemma-3 Finance Mix
-A lightweight **Gemma-3 270M** model fine-tuned for *financial Q&A, news-headline sentiment and retail-investor discourse*.
 ---

 # Gemma-3 Finance Mix
+A lightweight **Gemma-3 270M** model fine-tuned for *financial Q&A, causal-lm/finance, news-headline sentiment and retail-investor discourse*.
 ---