Instructions to use ZedLow/smolvlm-receipt-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ZedLow/smolvlm-receipt-parser with Transformers:

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

pipe = pipeline("image-text-to-text", model="ZedLow/smolvlm-receipt-parser")
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, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("ZedLow/smolvlm-receipt-parser")
model = AutoModelForImageTextToText.from_pretrained("ZedLow/smolvlm-receipt-parser")
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 ZedLow/smolvlm-receipt-parser with vLLM:

Install from pip and serve model

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

SGLang

How to use ZedLow/smolvlm-receipt-parser 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 "ZedLow/smolvlm-receipt-parser" \
    --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": "ZedLow/smolvlm-receipt-parser",
		"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 "ZedLow/smolvlm-receipt-parser" \
        --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": "ZedLow/smolvlm-receipt-parser",
		"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 ZedLow/smolvlm-receipt-parser with Docker Model Runner:
```
docker model run hf.co/ZedLow/smolvlm-receipt-parser
```

ZedLow commited on Jan 29

Commit

fd11370

verified ·

1 Parent(s): 9609d7e

Upload processor

Browse files

Files changed (4) hide show

chat_template.jinja +2 -0
processor_config.json +31 -0
tokenizer.json +0 -0
tokenizer_config.json +27 -0

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ <\|im_start\|>{% for message in messages %}{{message['role'] \| capitalize}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'] == 'text' %}{{line['text']}}{% elif line['type'] == 'image' %}{{ '<image>' }}{% endif %}{% endfor %}<end_of_utterance>
2	+ {% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}

processor_config.json ADDED Viewed

	@@ -0,0 +1,31 @@

+{
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_image_splitting": true,
+    "do_normalize": true,
+    "do_pad": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Idefics3ImageProcessor",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "max_image_size": {
+      "longest_edge": 512
+    },
+    "resample": 1,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 2048
+    }
+  },
+  "image_seq_len": 64,
+  "processor_class": "Idefics3Processor"
+}

tokenizer.json ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,27 @@

+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|im_start|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<end_of_utterance>",
+  "extra_special_tokens": [
+    "<fake_token_around_image>",
+    "<image>",
+    "<end_of_utterance>"
+  ],
+  "is_local": true,
+  "legacy": false,
+  "max_length": 4096,
+  "model_max_length": 8192,
+  "pad_to_multiple_of": null,
+  "pad_token": "<|im_end|>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "processor_class": "Idefics3Processor",
+  "stride": 0,
+  "tokenizer_class": "TokenizersBackend",
+  "truncation_side": "left",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152
+}