Image-Text-to-Text
Transformers
Safetensors
English
qwen3_5
decision-model
typed-decisions
one-pass
option-probabilities
conversational
Instructions to use thegovind/blink-mimo-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thegovind/blink-mimo-9b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="thegovind/blink-mimo-9b") 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 AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("thegovind/blink-mimo-9b") model = AutoModelForMultimodalLM.from_pretrained("thegovind/blink-mimo-9b", 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=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thegovind/blink-mimo-9b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thegovind/blink-mimo-9b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thegovind/blink-mimo-9b", "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/thegovind/blink-mimo-9b
- SGLang
How to use thegovind/blink-mimo-9b 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 "thegovind/blink-mimo-9b" \ --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": "thegovind/blink-mimo-9b", "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 "thegovind/blink-mimo-9b" \ --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": "thegovind/blink-mimo-9b", "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 thegovind/blink-mimo-9b with Docker Model Runner:
docker model run hf.co/thegovind/blink-mimo-9b
File size: 3,916 Bytes
7c0a3b8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 | {%- macro render_value(value) -%}
{%- if value is string -%}
{{- value -}}
{%- else -%}
{{- value | tojson(ensure_ascii=False) -}}
{%- endif -%}
{%- endmacro -%}
{%- macro render_content(message_content) -%}
{%- if message_content is string -%}
{{- message_content -}}
{%- elif message_content is iterable -%}
{%- for part in message_content -%}
{%- if part is not mapping -%}
{{- part -}}
{%- elif part['type'] == 'image' or 'image' in part or 'image_url' in part -%}
{{- '<|vision_start|><|image_pad|><|vision_end|>' -}}
{%- elif part['type'] == 'audio' or part['type'] == 'input_audio' or 'audio' in part or 'audio_url' in part or 'input_audio' in part -%}
{{- '<|mimo_audio_start|><|audio_pad|><|mimo_audio_end|>' -}}
{%- elif part['type'] == 'video' or 'video' in part or 'video_url' in part -%}
{{- '<|vision_start|><|video_pad|><|vision_end|>' -}}
{%- elif 'text' in part -%}
{{- part['text'] -}}
{%- endif -%}
{%- endfor -%}
{%- endif -%}
{%- endmacro -%}
{%- macro render_tools(tools) -%}
{{- 'You are provided with the following tools:\n\n<tools>' -}}
{%- for tool in tools -%}
{{- '\n' ~ (tool | tojson(ensure_ascii=False)) -}}
{%- endfor -%}
{{- '\n</tools>' -}}
{%- endmacro -%}
{%- macro render_tool_calls(tool_calls) -%}
{%- for tool_call in tool_calls -%}
{%- if tool_call.function is defined -%}
{%- set tool_call = tool_call.function -%}
{%- elif tool_call.custom is defined -%}
{%- set tool_call = tool_call.custom -%}
{%- endif -%}
{{- '<tool_call><function=' ~ tool_call.name ~ '>' -}}
{%- if tool_call.input is defined and tool_call.input is string -%}
{{- tool_call.input -}}
{%- elif tool_call.arguments -%}
{%- if tool_call.arguments is string -%}
{{- tool_call.arguments -}}
{%- else -%}
{%- for args_name, args_value in tool_call.arguments | items -%}
{{- '<parameter=' ~ args_name ~ '>' ~ render_value(args_value) ~ '</parameter>' -}}
{%- endfor -%}
{%- endif -%}
{%- endif -%}
{{- '</function></tool_call>' -}}
{%- endfor -%}
{%- endmacro -%}
{%- macro render_assistant_message(message) -%}
{%- generation -%}
{%- set content = render_content(message.content) -%}
{%- set reasoning = message.reasoning_content if message.reasoning_content is string else '' -%}
{{- '<|im_start|>assistant\n<think>' ~ reasoning ~ '</think>' ~ content -}}
{%- if message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 -%}
{{- render_tool_calls(message.tool_calls) -}}
{%- endif -%}
{{- '<|im_end|>' -}}
{%- endgeneration -%}
{%- endmacro -%}
{%- if tools is defined and tools is iterable and tools | length > 0 -%}
{{- '<|im_start|>system\n' ~ render_tools(tools) ~ '<|im_end|>' -}}
{%- endif -%}
{%- for message in messages -%}
{%- if message.role == 'assistant' -%}
{{- render_assistant_message(message) -}}
{%- else -%}
{%- set body = render_content(message.content) -%}
{{- '<|im_start|>' ~ message.role ~ '\n' ~ body -}}
{%- if message.tools is defined and message.tools is iterable and message.tools | length > 0 -%}
{%- if body -%}
{{- '\n\n' -}}
{%- endif -%}
{{- render_tools(message.tools) -}}
{%- endif -%}
{{- '<|im_end|>' -}}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
{{- '<|im_start|>assistant\n' -}}
{%- if enable_thinking is false -%}
{{- '<think></think>' -}}
{%- endif -%}
{%- endif -%}
|