Image-Text-to-Text
Transformers
Safetensors
English
vision
vlm
vision-language-model
image-text
instruction-tuning
dpo
lora
custom-architecture
conversational
Instructions to use mkd-dev/keural-VLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkd-dev/keural-VLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="mkd-dev/keural-VLM") 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 AutoModel model = AutoModel.from_pretrained("mkd-dev/keural-VLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mkd-dev/keural-VLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mkd-dev/keural-VLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mkd-dev/keural-VLM", "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/mkd-dev/keural-VLM
- SGLang
How to use mkd-dev/keural-VLM 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 "mkd-dev/keural-VLM" \ --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": "mkd-dev/keural-VLM", "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 "mkd-dev/keural-VLM" \ --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": "mkd-dev/keural-VLM", "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 mkd-dev/keural-VLM with Docker Model Runner:
docker model run hf.co/mkd-dev/keural-VLM
Download chat_template.jinja from mkd-dev/keural-VLM: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/mkd-dev/keural-VLM/resolve/main/chat_template.jinja
- Command line
-
hf download hf://mkd-dev/keural-VLM/chat_template.jinja
-
curl -L -o chat_template.jinja https://huggingface.co/mkd-dev/keural-VLM/resolve/main/chat_template.jinja
3.96 kB
| {%- if messages[0]["role"] == "system" %} | |
| {%- set system_message = messages[0]["content"] %} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set loop_messages = messages %} | |
| {%- endif %} | |
| {%- if not tools is defined %} | |
| {%- set tools = none %} | |
| {%- endif %} | |
| {%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %} | |
| {#- This block checks for alternating user/assistant messages, skipping tool calling messages #} | |
| {%- set ns = namespace() %} | |
| {%- set ns.index = 0 %} | |
| {%- for message in loop_messages %} | |
| {%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %} | |
| {%- if (message["role"] == "user") != (ns.index % 2 == 0) %} | |
| {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }} | |
| {%- endif %} | |
| {%- set ns.index = ns.index + 1 %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- bos_token }} | |
| {%- for message in loop_messages %} | |
| {%- if message["role"] == "user" %} | |
| {%- if tools is not none and (message == user_messages[-1]) %} | |
| {{- "[AVAILABLE_TOOLS] [" }} | |
| {%- for tool in tools %} | |
| {%- set tool = tool.function %} | |
| {{- '{"type": "function", "function": {' }} | |
| {%- for key, val in tool.items() if key != "return" %} | |
| {%- if val is string %} | |
| {{- '"' + key + '": "' + val + '"' }} | |
| {%- else %} | |
| {{- '"' + key + '": ' + val|tojson }} | |
| {%- endif %} | |
| {%- if not loop.last %} | |
| {{- ", " }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- "}}" }} | |
| {%- if not loop.last %} | |
| {{- ", " }} | |
| {%- else %} | |
| {{- "]" }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- "[/AVAILABLE_TOOLS]" }} | |
| {%- endif %} | |
| {%- if loop.last and system_message is defined %} | |
| {{- "[INST] " + system_message + "\n\n" + message["content"] + "[/INST]" }} | |
| {%- else %} | |
| {{- "[INST] " + message["content"] + "[/INST]" }} | |
| {%- endif %} | |
| {%- elif message.tool_calls is defined and message.tool_calls is not none %} | |
| {{- "[TOOL_CALLS] [" }} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- set out = tool_call.function|tojson %} | |
| {{- out[:-1] }} | |
| {%- if not tool_call.id is defined or tool_call.id|length != 9 %} | |
| {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }} | |
| {%- endif %} | |
| {{- ', "id": "' + tool_call.id + '"}' }} | |
| {%- if not loop.last %} | |
| {{- ", " }} | |
| {%- else %} | |
| {{- "]" + eos_token }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- elif message["role"] == "assistant" %} | |
| {{- " " + message["content"]|trim + eos_token}} | |
| {%- elif message["role"] == "tool_results" or message["role"] == "tool" %} | |
| {%- if message.content is defined and message.content.content is defined %} | |
| {%- set content = message.content.content %} | |
| {%- else %} | |
| {%- set content = message.content %} | |
| {%- endif %} | |
| {{- '[TOOL_RESULTS] {"content": ' + content|string + ", " }} | |
| {%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %} | |
| {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }} | |
| {%- endif %} | |
| {{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }} | |
| {%- else %} | |
| {{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }} | |
| {%- endif %} | |
| {%- endfor %} | |