Instructions to use chipherndon/Infinity-Parser2-Flash-vllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chipherndon/Infinity-Parser2-Flash-vllm with Transformers:

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

pipe = pipeline("image-text-to-text", model="chipherndon/Infinity-Parser2-Flash-vllm")
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("chipherndon/Infinity-Parser2-Flash-vllm")
model = AutoModelForMultimodalLM.from_pretrained("chipherndon/Infinity-Parser2-Flash-vllm", 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 chipherndon/Infinity-Parser2-Flash-vllm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chipherndon/Infinity-Parser2-Flash-vllm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chipherndon/Infinity-Parser2-Flash-vllm",
		"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/chipherndon/Infinity-Parser2-Flash-vllm

SGLang

How to use chipherndon/Infinity-Parser2-Flash-vllm 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 "chipherndon/Infinity-Parser2-Flash-vllm" \
    --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": "chipherndon/Infinity-Parser2-Flash-vllm",
		"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 "chipherndon/Infinity-Parser2-Flash-vllm" \
        --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": "chipherndon/Infinity-Parser2-Flash-vllm",
		"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 chipherndon/Infinity-Parser2-Flash-vllm with Docker Model Runner:
```
docker model run hf.co/chipherndon/Infinity-Parser2-Flash-vllm
```

chipherndon commited on 15 days ago

Commit

9e31685

verified ·

1 Parent(s): 4368c9c

Patch tokenizer_class TokenizersBackend -> Qwen2Tokenizer for vLLM/transformers 4.x

Browse files

Files changed (1) hide show

tokenizer_config.json +23 -23

tokenizer_config.json CHANGED Viewed

@@ -1,32 +1,32 @@
 {
-  "add_prefix_space": false,
-  "audio_bos_token": "<|audio_start|>",
-  "audio_eos_token": "<|audio_end|>",
-  "audio_token": "<|audio_pad|>",
-  "backend": "tokenizers",
-  "bos_token": null,
-  "clean_up_tokenization_spaces": false,
-  "eos_token": "<|im_end|>",
-  "errors": "replace",
-  "image_token": "<|image_pad|>",
-  "is_local": true,
-  "model_max_length": 262144,
-  "model_specific_special_tokens": {
     "audio_bos_token": "<|audio_start|>",
     "audio_eos_token": "<|audio_end|>",
     "audio_token": "<|audio_pad|>",
     "image_token": "<|image_pad|>",
     "video_token": "<|video_pad|>",
     "vision_bos_token": "<|vision_start|>",
     "vision_eos_token": "<|vision_end|>"
-  },
-  "pad_token": "<|endoftext|>",
-  "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
-  "processor_class": "Qwen3VLProcessor",
-  "split_special_tokens": false,
-  "tokenizer_class": "TokenizersBackend",
-  "unk_token": null,
-  "video_token": "<|video_pad|>",
-  "vision_bos_token": "<|vision_start|>",
-  "vision_eos_token": "<|vision_end|>"
 }

 {
+    "add_prefix_space": false,
     "audio_bos_token": "<|audio_start|>",
     "audio_eos_token": "<|audio_end|>",
     "audio_token": "<|audio_pad|>",
+    "backend": "tokenizers",
+    "bos_token": null,
+    "clean_up_tokenization_spaces": false,
+    "eos_token": "<|im_end|>",
+    "errors": "replace",
     "image_token": "<|image_pad|>",
+    "is_local": true,
+    "model_max_length": 262144,
+    "model_specific_special_tokens": {
+        "audio_bos_token": "<|audio_start|>",
+        "audio_eos_token": "<|audio_end|>",
+        "audio_token": "<|audio_pad|>",
+        "image_token": "<|image_pad|>",
+        "video_token": "<|video_pad|>",
+        "vision_bos_token": "<|vision_start|>",
+        "vision_eos_token": "<|vision_end|>"
+    },
+    "pad_token": "<|endoftext|>",
+    "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+    "processor_class": "Qwen3VLProcessor",
+    "split_special_tokens": false,
+    "tokenizer_class": "Qwen2Tokenizer",
+    "unk_token": null,
     "video_token": "<|video_pad|>",
     "vision_bos_token": "<|vision_start|>",
     "vision_eos_token": "<|vision_end|>"
 }