Image-Text-to-Text
Transformers
Safetensors
monarch_gemma4
gemma4
monarch-matrices
model-compression
conversational
custom_code
Instructions to use hexoy/gemma-4-e2b-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hexoy/gemma-4-e2b-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hexoy/gemma-4-e2b-distilled", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("hexoy/gemma-4-e2b-distilled", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hexoy/gemma-4-e2b-distilled with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hexoy/gemma-4-e2b-distilled" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hexoy/gemma-4-e2b-distilled", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/hexoy/gemma-4-e2b-distilled
- SGLang
How to use hexoy/gemma-4-e2b-distilled 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 "hexoy/gemma-4-e2b-distilled" \ --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": "hexoy/gemma-4-e2b-distilled", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "hexoy/gemma-4-e2b-distilled" \ --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": "hexoy/gemma-4-e2b-distilled", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use hexoy/gemma-4-e2b-distilled with Docker Model Runner:
docker model run hf.co/hexoy/gemma-4-e2b-distilled
| from transformers import Gemma4ForConditionalGeneration | |
| from .configuration_monarch_gemma4 import MonarchGemma4Config | |
| from .monarch import replace_linear_with_monarch | |
| class MonarchGemma4ForConditionalGeneration(Gemma4ForConditionalGeneration): | |
| """Gemma 4 with configured language-model MLPs stored as Monarch factors.""" | |
| config_class = MonarchGemma4Config | |
| def __init__(self, config: MonarchGemma4Config): | |
| super().__init__(config) | |
| layers = self.model.language_model.layers | |
| for layer_index in config.monarch_compressed_layers: | |
| if layer_index < 0 or layer_index >= len(layers): | |
| raise ValueError( | |
| f"compressed layer index {layer_index} is outside the language model's " | |
| f"0..{len(layers) - 1} range" | |
| ) | |
| replace_linear_with_monarch( | |
| layers[layer_index].mlp, | |
| config.monarch_blocks_weights, | |
| init_method="identity_noise", | |
| module_path=f"model.language_model.layers.{layer_index}.mlp", | |
| ) | |