Image-Text-to-Text
Transformers
Safetensors
sentence-transformers
English
French
qwen3_5
reranker
cross-encoder
multimodal
text-ranking
document-reranking
vidore
beir
conversational
🇪🇺 Region: EU
Instructions to use lightonai/LightOn-rerank-PW-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lightonai/LightOn-rerank-PW-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="lightonai/LightOn-rerank-PW-4B") 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("lightonai/LightOn-rerank-PW-4B") model = AutoModelForMultimodalLM.from_pretrained("lightonai/LightOn-rerank-PW-4B", 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]:])) - sentence-transformers
How to use lightonai/LightOn-rerank-PW-4B with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("lightonai/LightOn-rerank-PW-4B") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lightonai/LightOn-rerank-PW-4B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lightonai/LightOn-rerank-PW-4B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lightonai/LightOn-rerank-PW-4B", "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/lightonai/LightOn-rerank-PW-4B
- SGLang
How to use lightonai/LightOn-rerank-PW-4B 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 "lightonai/LightOn-rerank-PW-4B" \ --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": "lightonai/LightOn-rerank-PW-4B", "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 "lightonai/LightOn-rerank-PW-4B" \ --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": "lightonai/LightOn-rerank-PW-4B", "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 lightonai/LightOn-rerank-PW-4B with Docker Model Runner:
docker model run hf.co/lightonai/LightOn-rerank-PW-4B
Upload model weights
Browse files- .gitattributes +1 -0
- chat_template.jinja +154 -0
- config.json +109 -0
- generation_config.json +6 -0
- model.safetensors +3 -0
- processor_config.json +60 -0
- tokenizer.json +3 -0
- tokenizer_config.json +32 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja
ADDED
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@@ -0,0 +1,154 @@
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| 1 |
+
{%- set image_count = namespace(value=0) %}
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| 2 |
+
{%- set video_count = namespace(value=0) %}
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| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
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| 4 |
+
{%- if content is string %}
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| 5 |
+
{{- content }}
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| 6 |
+
{%- elif content is iterable and content is not mapping %}
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| 7 |
+
{%- for item in content %}
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| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
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| 9 |
+
{%- if is_system_content %}
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| 10 |
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{{- raise_exception('System message cannot contain images.') }}
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| 11 |
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{%- endif %}
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| 12 |
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{%- if do_vision_count %}
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| 13 |
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{%- set image_count.value = image_count.value + 1 %}
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| 14 |
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{%- endif %}
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| 15 |
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{%- if add_vision_id %}
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| 16 |
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{{- 'Picture ' ~ image_count.value ~ ': ' }}
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| 17 |
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{%- endif %}
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| 18 |
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{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
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| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
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| 20 |
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{%- if is_system_content %}
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| 21 |
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{{- raise_exception('System message cannot contain videos.') }}
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| 22 |
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{%- endif %}
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| 23 |
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{%- if do_vision_count %}
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| 24 |
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{%- set video_count.value = video_count.value + 1 %}
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| 25 |
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{%- endif %}
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| 26 |
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{%- if add_vision_id %}
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| 27 |
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{{- 'Video ' ~ video_count.value ~ ': ' }}
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| 28 |
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{%- endif %}
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| 29 |
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{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
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| 30 |
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{%- elif 'text' in item %}
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| 31 |
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{{- item.text }}
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| 32 |
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{%- else %}
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| 33 |
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{{- raise_exception('Unexpected item type in content.') }}
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| 34 |
+
{%- endif %}
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| 35 |
+
{%- endfor %}
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| 36 |
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{%- elif content is none or content is undefined %}
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| 37 |
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{{- '' }}
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| 38 |
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{%- else %}
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| 39 |
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{{- raise_exception('Unexpected content type.') }}
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| 40 |
+
{%- endif %}
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| 41 |
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{%- endmacro %}
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| 42 |
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{%- if not messages %}
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| 43 |
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{{- raise_exception('No messages provided.') }}
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| 44 |
+
{%- endif %}
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| 45 |
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{%- if tools and tools is iterable and tools is not mapping %}
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| 46 |
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{{- '<|im_start|>system\n' }}
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| 47 |
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{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
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| 48 |
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{%- for tool in tools %}
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{{- "\n" }}
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| 50 |
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{{- tool | tojson }}
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{%- endfor %}
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| 52 |
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{{- "\n</tools>" }}
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{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
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| 54 |
+
{%- if messages[0].role == 'system' %}
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{%- set content = render_content(messages[0].content, false, true)|trim %}
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| 56 |
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{%- if content %}
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{{- '\n\n' + content }}
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+
{%- endif %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- else %}
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+
{%- if messages[0].role == 'system' %}
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{%- set content = render_content(messages[0].content, false, true)|trim %}
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{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" %}
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| 71 |
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{%- set content = render_content(message.content, false)|trim %}
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{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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| 75 |
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{%- endif %}
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{%- endif %}
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| 77 |
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{%- endfor %}
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| 78 |
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{%- if ns.multi_step_tool %}
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| 79 |
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{{- raise_exception('No user query found in messages.') }}
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| 80 |
+
{%- endif %}
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| 81 |
+
{%- for message in messages %}
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{%- set content = render_content(message.content, true)|trim %}
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| 83 |
+
{%- if message.role == "system" %}
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| 84 |
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{%- if not loop.first %}
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| 85 |
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{{- raise_exception('System message must be at the beginning.') }}
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| 86 |
+
{%- endif %}
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| 87 |
+
{%- elif message.role == "user" %}
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| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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| 89 |
+
{%- elif message.role == "assistant" %}
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| 90 |
+
{%- set reasoning_content = '' %}
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| 91 |
+
{%- if message.reasoning_content is string %}
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| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
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| 93 |
+
{%- else %}
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| 94 |
+
{%- if '</think>' in content %}
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| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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| 97 |
+
{%- endif %}
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| 98 |
+
{%- endif %}
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| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
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| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
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| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
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| 102 |
+
{%- else %}
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| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
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| 104 |
+
{%- endif %}
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| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
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| 106 |
+
{%- for tool_call in message.tool_calls %}
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| 107 |
+
{%- if tool_call.function is defined %}
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| 108 |
+
{%- set tool_call = tool_call.function %}
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| 109 |
+
{%- endif %}
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| 110 |
+
{%- if loop.first %}
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| 111 |
+
{%- if content|trim %}
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| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
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| 113 |
+
{%- else %}
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| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
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| 116 |
+
{%- else %}
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| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
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| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
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| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
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| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
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| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
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| 130 |
+
{{- '<|im_end|>\n' }}
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| 131 |
+
{%- elif message.role == "tool" %}
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| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
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| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
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| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
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| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
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| 139 |
+
{{- '<|im_end|>\n' }}
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| 140 |
+
{%- elif loop.last %}
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| 141 |
+
{{- '<|im_end|>\n' }}
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| 142 |
+
{%- endif %}
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| 143 |
+
{%- else %}
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| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
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| 146 |
+
{%- endfor %}
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| 147 |
+
{%- if add_generation_prompt %}
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| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
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| 154 |
+
{%- endif %}
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config.json
ADDED
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@@ -0,0 +1,109 @@
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|
|
|
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|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForConditionalGeneration"
|
| 4 |
+
],
|
| 5 |
+
"dtype": "bfloat16",
|
| 6 |
+
"image_token_id": 248056,
|
| 7 |
+
"model_type": "qwen3_5",
|
| 8 |
+
"text_config": {
|
| 9 |
+
"attention_bias": false,
|
| 10 |
+
"attention_dropout": 0.0,
|
| 11 |
+
"attn_output_gate": true,
|
| 12 |
+
"bos_token_id": null,
|
| 13 |
+
"dtype": "bfloat16",
|
| 14 |
+
"eos_token_id": 248044,
|
| 15 |
+
"full_attention_interval": 4,
|
| 16 |
+
"head_dim": 256,
|
| 17 |
+
"hidden_act": "silu",
|
| 18 |
+
"hidden_size": 2560,
|
| 19 |
+
"initializer_range": 0.02,
|
| 20 |
+
"intermediate_size": 9216,
|
| 21 |
+
"layer_types": [
|
| 22 |
+
"linear_attention",
|
| 23 |
+
"linear_attention",
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"full_attention",
|
| 26 |
+
"linear_attention",
|
| 27 |
+
"linear_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"full_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
+
"linear_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"full_attention",
|
| 34 |
+
"linear_attention",
|
| 35 |
+
"linear_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"full_attention",
|
| 38 |
+
"linear_attention",
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"full_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"full_attention",
|
| 46 |
+
"linear_attention",
|
| 47 |
+
"linear_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"full_attention",
|
| 50 |
+
"linear_attention",
|
| 51 |
+
"linear_attention",
|
| 52 |
+
"linear_attention",
|
| 53 |
+
"full_attention"
|
| 54 |
+
],
|
| 55 |
+
"linear_conv_kernel_dim": 4,
|
| 56 |
+
"linear_key_head_dim": 128,
|
| 57 |
+
"linear_num_key_heads": 16,
|
| 58 |
+
"linear_num_value_heads": 32,
|
| 59 |
+
"linear_value_head_dim": 128,
|
| 60 |
+
"mamba_ssm_dtype": "float32",
|
| 61 |
+
"max_position_embeddings": 262144,
|
| 62 |
+
"mlp_only_layers": [],
|
| 63 |
+
"model_type": "qwen3_5_text",
|
| 64 |
+
"mtp_num_hidden_layers": 1,
|
| 65 |
+
"mtp_use_dedicated_embeddings": false,
|
| 66 |
+
"num_attention_heads": 16,
|
| 67 |
+
"num_hidden_layers": 32,
|
| 68 |
+
"num_key_value_heads": 4,
|
| 69 |
+
"pad_token_id": null,
|
| 70 |
+
"partial_rotary_factor": 0.25,
|
| 71 |
+
"rms_norm_eps": 1e-06,
|
| 72 |
+
"rope_parameters": {
|
| 73 |
+
"mrope_interleaved": true,
|
| 74 |
+
"mrope_section": [
|
| 75 |
+
11,
|
| 76 |
+
11,
|
| 77 |
+
10
|
| 78 |
+
],
|
| 79 |
+
"partial_rotary_factor": 0.25,
|
| 80 |
+
"rope_theta": 10000000,
|
| 81 |
+
"rope_type": "default"
|
| 82 |
+
},
|
| 83 |
+
"tie_word_embeddings": true,
|
| 84 |
+
"use_cache": true,
|
| 85 |
+
"vocab_size": 248320
|
| 86 |
+
},
|
| 87 |
+
"tie_word_embeddings": true,
|
| 88 |
+
"transformers_version": "5.4.0",
|
| 89 |
+
"video_token_id": 248057,
|
| 90 |
+
"vision_config": {
|
| 91 |
+
"deepstack_visual_indexes": [],
|
| 92 |
+
"depth": 24,
|
| 93 |
+
"dtype": "bfloat16",
|
| 94 |
+
"hidden_act": "gelu_pytorch_tanh",
|
| 95 |
+
"hidden_size": 1024,
|
| 96 |
+
"in_channels": 3,
|
| 97 |
+
"initializer_range": 0.02,
|
| 98 |
+
"intermediate_size": 4096,
|
| 99 |
+
"model_type": "qwen3_5",
|
| 100 |
+
"num_heads": 16,
|
| 101 |
+
"num_position_embeddings": 2304,
|
| 102 |
+
"out_hidden_size": 2560,
|
| 103 |
+
"patch_size": 16,
|
| 104 |
+
"spatial_merge_size": 2,
|
| 105 |
+
"temporal_patch_size": 2
|
| 106 |
+
},
|
| 107 |
+
"vision_end_token_id": 248054,
|
| 108 |
+
"vision_start_token_id": 248053
|
| 109 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"eos_token_id": 248044,
|
| 4 |
+
"transformers_version": "5.4.0",
|
| 5 |
+
"use_cache": true
|
| 6 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:54f58245c6fd1fcaeab8507903220731659804195b3cdbb0b85bc4c1e68442b8
|
| 3 |
+
size 9078620504
|
processor_config.json
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_normalize": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"do_resize": true,
|
| 7 |
+
"image_mean": [
|
| 8 |
+
0.5,
|
| 9 |
+
0.5,
|
| 10 |
+
0.5
|
| 11 |
+
],
|
| 12 |
+
"image_processor_type": "Qwen2VLImageProcessor",
|
| 13 |
+
"image_std": [
|
| 14 |
+
0.5,
|
| 15 |
+
0.5,
|
| 16 |
+
0.5
|
| 17 |
+
],
|
| 18 |
+
"merge_size": 2,
|
| 19 |
+
"patch_size": 16,
|
| 20 |
+
"resample": 3,
|
| 21 |
+
"rescale_factor": 0.00392156862745098,
|
| 22 |
+
"size": {
|
| 23 |
+
"longest_edge": 16777216,
|
| 24 |
+
"shortest_edge": 65536
|
| 25 |
+
},
|
| 26 |
+
"temporal_patch_size": 2
|
| 27 |
+
},
|
| 28 |
+
"processor_class": "Qwen3VLProcessor",
|
| 29 |
+
"video_processor": {
|
| 30 |
+
"do_convert_rgb": true,
|
| 31 |
+
"do_normalize": true,
|
| 32 |
+
"do_rescale": true,
|
| 33 |
+
"do_resize": true,
|
| 34 |
+
"do_sample_frames": true,
|
| 35 |
+
"fps": 2,
|
| 36 |
+
"image_mean": [
|
| 37 |
+
0.5,
|
| 38 |
+
0.5,
|
| 39 |
+
0.5
|
| 40 |
+
],
|
| 41 |
+
"image_std": [
|
| 42 |
+
0.5,
|
| 43 |
+
0.5,
|
| 44 |
+
0.5
|
| 45 |
+
],
|
| 46 |
+
"max_frames": 768,
|
| 47 |
+
"merge_size": 2,
|
| 48 |
+
"min_frames": 4,
|
| 49 |
+
"patch_size": 16,
|
| 50 |
+
"resample": 3,
|
| 51 |
+
"rescale_factor": 0.00392156862745098,
|
| 52 |
+
"return_metadata": false,
|
| 53 |
+
"size": {
|
| 54 |
+
"longest_edge": 25165824,
|
| 55 |
+
"shortest_edge": 4096
|
| 56 |
+
},
|
| 57 |
+
"temporal_patch_size": 2,
|
| 58 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 59 |
+
}
|
| 60 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:87a7830d63fcf43bf241c3c5242e96e62dd3fdc29224ca26fed8ea333db72de4
|
| 3 |
+
size 19989343
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|im_end|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"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+",
|
| 25 |
+
"processor_class": "Qwen3VLProcessor",
|
| 26 |
+
"split_special_tokens": false,
|
| 27 |
+
"tokenizer_class": "TokenizersBackend",
|
| 28 |
+
"unk_token": null,
|
| 29 |
+
"video_token": "<|video_pad|>",
|
| 30 |
+
"vision_bos_token": "<|vision_start|>",
|
| 31 |
+
"vision_eos_token": "<|vision_end|>"
|
| 32 |
+
}
|