Image-Text-to-Text
Transformers
Safetensors
gemma3n
automatic-speech-recognition
automatic-speech-translation
audio-text-to-text
video-text-to-text
Instructions to use google/gemma-3n-E4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-3n-E4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="google/gemma-3n-E4B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/gemma-3n-E4B") model = AutoModelForImageTextToText.from_pretrained("google/gemma-3n-E4B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use google/gemma-3n-E4B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-3n-E4B" # 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-3n-E4B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/gemma-3n-E4B
- SGLang
How to use google/gemma-3n-E4B 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-3n-E4B" \ --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-3n-E4B", "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-3n-E4B" \ --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-3n-E4B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/gemma-3n-E4B with Docker Model Runner:
docker model run hf.co/google/gemma-3n-E4B
Can't run the basic notebook fork on kaggle
#5
by moaz-eldefrawy - opened
after running:
!pip install -U transformers
and
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-text-to-text", model="google/gemma-3n-E4B")
I get:
ValueError Traceback (most recent call last)
/tmp/ipykernel_36/2518710844.py in <cell line: 0>()
2 from transformers import pipeline
3
----> 4 pipe = pipeline("image-text-to-text", model="google/gemma-3n-E4B")
/usr/local/lib/python3.11/dist-packages/transformers/pipelines/__init__.py in pipeline(task, model, config, tokenizer, feature_extractor, image_processor, processor, framework, revision, use_fast, token, device, device_map, torch_dtype, trust_remote_code, model_kwargs, pipeline_class, **kwargs)
1028 if isinstance(model, str) or framework is None:
1029 model_classes = {"tf": targeted_task["tf"], "pt": targeted_task["pt"]}
-> 1030 framework, model = infer_framework_load_model(
1031 adapter_path if adapter_path is not None else model,
1032 model_classes=model_classes,
/usr/local/lib/python3.11/dist-packages/transformers/pipelines/base.py in infer_framework_load_model(model, config, model_classes, task, framework, **model_kwargs)
330 for class_name, trace in all_traceback.items():
331 error += f"while loading with {class_name}, an error is thrown:\n{trace}\n"
--> 332 raise ValueError(
333 f"Could not load model {model} with any of the following classes: {class_tuple}. See the original errors:\n\n{error}\n"
334 )
ValueError: Could not load model google/gemma-3n-E4B with any of the following classes: (<class 'transformers.models.auto.modeling_auto.AutoModelForImageTextToText'>, <class 'transformers.models.gemma3n.modeling_gemma3n.Gemma3nForConditionalGeneration'>). See the original errors:
while loading with AutoModelForImageTextToText, an error is thrown:
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/transformers/pipelines/base.py", line 292, in infer_framework_load_model
model = model_class.from_pretrained(model, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 600, in from_pretrained
return model_class.from_pretrained(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 4766, in from_pretrained
model = cls(config, *model_args, **model_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 2207, in __init__
self.model = Gemma3nModel(config)
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 1959, in __init__
self.vision_tower = AutoModel.from_config(config=config.vision_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 456, in from_config
return model_class._from_config(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 2208, in _from_config
model = cls(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/timm_wrapper/modeling_timm_wrapper.py", line 120, in __init__
self.timm_model = timm.create_model(config.architecture, pretrained=False, num_classes=0, **extra_init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/timm/models/_factory.py", line 122, in create_model
raise RuntimeError('Unknown model (%s)' % model_name)
RuntimeError: Unknown model (mobilenetv5_300m_enc)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/transformers/pipelines/base.py", line 310, in infer_framework_load_model
model = model_class.from_pretrained(model, **fp32_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 600, in from_pretrained
return model_class.from_pretrained(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 4766, in from_pretrained
model = cls(config, *model_args, **model_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 2207, in __init__
self.model = Gemma3nModel(config)
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 1959, in __init__
self.vision_tower = AutoModel.from_config(config=config.vision_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 456, in from_config
return model_class._from_config(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 2208, in _from_config
model = cls(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/timm_wrapper/modeling_timm_wrapper.py", line 120, in __init__
self.timm_model = timm.create_model(config.architecture, pretrained=False, num_classes=0, **extra_init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/timm/models/_factory.py", line 122, in create_model
raise RuntimeError('Unknown model (%s)' % model_name)
RuntimeError: Unknown model (mobilenetv5_300m_enc)
while loading with Gemma3nForConditionalGeneration, an error is thrown:
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/transformers/pipelines/base.py", line 292, in infer_framework_load_model
model = model_class.from_pretrained(model, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 4766, in from_pretrained
model = cls(config, *model_args, **model_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 2207, in __init__
self.model = Gemma3nModel(config)
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 1959, in __init__
self.vision_tower = AutoModel.from_config(config=config.vision_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 456, in from_config
return model_class._from_config(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 2208, in _from_config
model = cls(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/timm_wrapper/modeling_timm_wrapper.py", line 120, in __init__
self.timm_model = timm.create_model(config.architecture, pretrained=False, num_classes=0, **extra_init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/timm/models/_factory.py", line 122, in create_model
raise RuntimeError('Unknown model (%s)' % model_name)
RuntimeError: Unknown model (mobilenetv5_300m_enc)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/transformers/pipelines/base.py", line 310, in infer_framework_load_model
model = model_class.from_pretrained(model, **fp32_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 4766, in from_pretrained
model = cls(config, *model_args, **model_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 2207, in __init__
self.model = Gemma3nModel(config)
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/gemma3n/modeling_gemma3n.py", line 1959, in __init__
self.vision_tower = AutoModel.from_config(config=config.vision_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/auto/auto_factory.py", line 456, in from_config
return model_class._from_config(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 311, in _wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/modeling_utils.py", line 2208, in _from_config
model = cls(config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/transformers/models/timm_wrapper/modeling_timm_wrapper.py", line 120, in __init__
self.timm_model = timm.create_model(config.architecture, pretrained=False, num_classes=0, **extra_init_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/timm/models/_factory.py", line 122, in create_model
raise RuntimeError('Unknown model (%s)' % model_name)
RuntimeError: Unknown model (mobilenetv5_300m_enc)
Hi @moaz-eldefrawy ,
Apologies for the late reply, the RuntimeError: Unknown model (mobilenetv5_300m_enc) is due to the older version of the timm. Could you please retry after upgrading the 'timm to the latest version along with the other libraries like 'torch, torchvision, torchaudio, timm, triton, transformers, accelerate by running the pip install -U torch torchvision, torchaudio timm triton transformers accelerate command. Please let me know if you required any additional assistance.
Thanks.