Medgemma-4B-NPU2

Instructions to use OpenFlowLM/Medgemma-4B-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenFlowLM/Medgemma-4B-NPU2 with Transformers:

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

pipe = pipeline("image-text-to-text", model="OpenFlowLM/Medgemma-4B-NPU2")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("OpenFlowLM/Medgemma-4B-NPU2")
model = AutoModelForMultimodalLM.from_pretrained("OpenFlowLM/Medgemma-4B-NPU2", device_map="auto")
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?"}
        ]
    },
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OpenFlowLM/Medgemma-4B-NPU2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenFlowLM/Medgemma-4B-NPU2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenFlowLM/Medgemma-4B-NPU2",
		"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/OpenFlowLM/Medgemma-4B-NPU2

SGLang

How to use OpenFlowLM/Medgemma-4B-NPU2 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 "OpenFlowLM/Medgemma-4B-NPU2" \
    --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": "OpenFlowLM/Medgemma-4B-NPU2",
		"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 "OpenFlowLM/Medgemma-4B-NPU2" \
        --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": "OpenFlowLM/Medgemma-4B-NPU2",
		"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 OpenFlowLM/Medgemma-4B-NPU2 with Docker Model Runner:
```
docker model run hf.co/OpenFlowLM/Medgemma-4B-NPU2
```

Medgemma-4B-NPU2 / config.json

Atomic-Germ

Duplicate from Atomic-Germ/Medgemma-4B-NPU2

3ecb5f0 12 days ago

Raw History Blame Contribute Delete

1.35 kB

{
  "architectures": [
    "Gemma3ForConditionalGeneration"
  ],
  "boi_token_index": 255999,
  "eoi_token_index": 256000,
  "image_token_index": 262144,
  "initializer_range": 0.02,
  "mm_tokens_per_image": 256,
  "model_type": "gemma3_text",
  "torch_dtype": "bfloat16",
  "transformers_version": "4.52.0.dev0",
  "attention_bias": false,
  "attention_dropout": 0.0,
  "attn_logit_softcapping": null,
  "cache_implementation": "hybrid",
  "final_logit_softcapping": null,
  "head_dim": 256,
  "hidden_activation": "gelu_pytorch_tanh",
  "hidden_size": 2560,
  "intermediate_size": 10240,
  "max_position_embeddings": 131072,
  "num_attention_heads": 8,
  "num_hidden_layers": 34,
  "num_key_value_heads": 4,
  "query_pre_attn_scalar": 256,
  "rms_norm_eps": 1e-06,
  "rope_local_base_freq": 10000,
  "rope_scaling": {
    "factor": 8.0,
    "rope_type": "linear"
  },
  "rope_theta": 1000000,
  "sliding_window": 1024,
  "sliding_window_pattern": 6,
  "use_cache": true,
  "vocab_size": 262208,
  "eos_token_id": 248044,
  "oflm_version": "0.1.0",
  "oflm_packed_with": "oflm pack -i /home/atomic-germ/.cache/huggingface/hub/models--mradermacher--medgemma-4b-it-i1-GGUF/snapshots/e72473b68139c8f77427dd21270eff3b2b80c1f9/medgemma-4b-it.i1-Q4_1.gguf -o /home/atomic-germ/Projects/OpenFlowLM-Next/Medgemma-4B-NPU2 -s Atomic-Germ/Medgemma-4B-NPU2"
}

	{
	"architectures": [
	"Gemma3ForConditionalGeneration"
	],
	"boi_token_index": 255999,
	"eoi_token_index": 256000,
	"image_token_index": 262144,
	"initializer_range": 0.02,
	"mm_tokens_per_image": 256,
	"model_type": "gemma3_text",
	"torch_dtype": "bfloat16",
	"transformers_version": "4.52.0.dev0",
	"attention_bias": false,
	"attention_dropout": 0.0,
	"attn_logit_softcapping": null,
	"cache_implementation": "hybrid",
	"final_logit_softcapping": null,
	"head_dim": 256,
	"hidden_activation": "gelu_pytorch_tanh",
	"hidden_size": 2560,
	"intermediate_size": 10240,
	"max_position_embeddings": 131072,
	"num_attention_heads": 8,
	"num_hidden_layers": 34,
	"num_key_value_heads": 4,
	"query_pre_attn_scalar": 256,
	"rms_norm_eps": 1e-06,
	"rope_local_base_freq": 10000,
	"rope_scaling": {
	"factor": 8.0,
	"rope_type": "linear"
	},
	"rope_theta": 1000000,
	"sliding_window": 1024,
	"sliding_window_pattern": 6,
	"use_cache": true,
	"vocab_size": 262208,
	"eos_token_id": 248044,
	"oflm_version": "0.1.0",
	"oflm_packed_with": "oflm pack -i /home/atomic-germ/.cache/huggingface/hub/models--mradermacher--medgemma-4b-it-i1-GGUF/snapshots/e72473b68139c8f77427dd21270eff3b2b80c1f9/medgemma-4b-it.i1-Q4_1.gguf -o /home/atomic-germ/Projects/OpenFlowLM-Next/Medgemma-4B-NPU2 -s Atomic-Germ/Medgemma-4B-NPU2"
	}