Instructions to use kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73 with Transformers:

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

pipe = pipeline("image-text-to-text", model="kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73")
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 AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73")
model = AutoModelForMultimodalLM.from_pretrained("kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73", 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 = processor.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=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73",
		"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/kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73

SGLang

How to use kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73 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 "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73" \
    --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": "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73",
		"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 "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73" \
        --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": "kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73",
		"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"
						}
					}
				]
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73 with Docker Model Runner:
```
docker model run hf.co/kairawal/Gemma-3-4B-IT-EL-SynthDolly-r16alpha128-E5-S73
```

kairawal commited on May 22

Commit

6d84e68

verified ·

1 Parent(s): d086569

Upload processor

Browse files

Files changed (4) hide show

chat_template.jinja +2 -2
preprocessor_config.json +29 -0
processor_config.json +4 -0
tokenizer_config.json +3 -4

chat_template.jinja CHANGED Viewed

@@ -42,6 +42,6 @@
 ' }}
 {%- endfor -%}
 {%- if add_generation_prompt -%}
-    {{ '<start_of_turn>model
-' }}
 {%- endif -%}

 ' }}
 {%- endfor -%}
 {%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
 {%- endif -%}

preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,29 @@

+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_pan_and_scan": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "Gemma3ImageProcessor",
+  "image_seq_length": 256,
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "pan_and_scan_max_num_crops": null,
+  "pan_and_scan_min_crop_size": null,
+  "pan_and_scan_min_ratio_to_activate": null,
+  "processor_class": "Gemma3Processor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 896,
+    "width": 896
+  }
+}

processor_config.json ADDED Viewed

	@@ -0,0 +1,4 @@

+{
+  "image_seq_length": 256,
+  "processor_class": "Gemma3Processor"
+}

tokenizer_config.json CHANGED Viewed

@@ -51336,12 +51336,11 @@
   "image_token": "<image_soft_token>",
   "model_max_length": 131072,
   "pad_token": "<pad>",
-  "padding_side": "right",
   "processor_class": "Gemma3Processor",
   "sp_model_kwargs": null,
   "spaces_between_special_tokens": false,
   "tokenizer_class": "GemmaTokenizer",
   "unk_token": "<unk>",
-  "use_default_system_prompt": false,
-  "chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{ '<start_of_turn>model\n' }}\n{%- endif -%}\n"
-}

   "image_token": "<image_soft_token>",
   "model_max_length": 131072,
   "pad_token": "<pad>",
+  "padding_side": "left",
   "processor_class": "Gemma3Processor",
   "sp_model_kwargs": null,
   "spaces_between_special_tokens": false,
   "tokenizer_class": "GemmaTokenizer",
   "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}