Image-Text-to-Text
Transformers
ONNX
Transformers.js
lfm2_vl
lfm2
vision
multimodal
food
calories
nutrition
conversational
Instructions to use opencal/opencal-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opencal/opencal-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="opencal/opencal-base") 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("opencal/opencal-base") model = AutoModelForMultimodalLM.from_pretrained("opencal/opencal-base", 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]:])) - Transformers.js
How to use opencal/opencal-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-text-to-text', 'opencal/opencal-base'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use opencal/opencal-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "opencal/opencal-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "opencal/opencal-base", "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/opencal/opencal-base
- SGLang
How to use opencal/opencal-base 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 "opencal/opencal-base" \ --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": "opencal/opencal-base", "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 "opencal/opencal-base" \ --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": "opencal/opencal-base", "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 opencal/opencal-base with Docker Model Runner:
docker model run hf.co/opencal/opencal-base
File size: 4,844 Bytes
4ecaaf8 | 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 | {
"backend": "tokenizers",
"bos_token": "<|startoftext|>",
"clean_up_tokenization_spaces": true,
"eos_token": "<|im_end|>",
"extra_special_tokens": [],
"image_end_token": "<|image_end|>",
"image_start_token": "<|image_start|>",
"image_thumbnail": "<|img_thumbnail|>",
"image_token": "<image>",
"is_local": true,
"legacy": false,
"local_files_only": false,
"model_max_length": 1000000000000000019884624838656,
"model_specific_special_tokens": {
"image_end_token": "<|image_end|>",
"image_start_token": "<|image_start|>",
"image_token": "<image>"
},
"pad_token": "<|pad|>",
"processor_class": "Lfm2VlProcessor",
"return_token_type_ids": false,
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "TokenizersBackend",
"use_default_system_prompt": false,
"use_fast": true,
"chat_template": "{{- bos_token -}}\n{%- set keep_past_thinking = keep_past_thinking | default(false) -%}\n\n{%- macro format_arg_value(arg_value) -%}\n {%- if arg_value is string -%}\n {{- '\"' + arg_value + '\"' -}}\n {%- elif arg_value is mapping -%}\n {{- arg_value | tojson -}}\n {%- else -%}\n {{- arg_value | string -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro parse_content(content) -%}\n {%- if content is string -%}\n {{- content -}}\n {%- else -%}\n {%- set _ns = namespace(result=\"\") -%}\n {%- for item in content -%}\n {%- if item.type == \"image\" -%}\n {%- set _ns.result = _ns.result + \"<image>\" -%}\n {%- elif item.type == \"text\" -%}\n {%- set _ns.result = _ns.result + item.text -%}\n {%- else -%}\n {%- set _ns.result = _ns.result + item | tojson -%}\n {%- endif -%}\n {%- endfor -%}\n {{- _ns.result -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro render_tool_calls(tool_calls) -%}\n {%- set tool_calls_ns = namespace(tool_calls=[]) -%}\n {%- for tool_call in tool_calls -%}\n {%- set func_name = tool_call.function.name -%}\n {%- set func_args = tool_call.function.arguments -%}\n {%- set args_ns = namespace(arg_strings=[]) -%}\n {%- for arg_name, arg_value in func_args.items() -%}\n {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + \"=\" + format_arg_value(arg_value)] -%}\n {%- endfor -%}\n {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + \"(\" + (args_ns.arg_strings | join(\", \")) + \")\"] -%}\n {%- endfor -%}\n {{- \"<|tool_call_start|>[\" + (tool_calls_ns.tool_calls | join(\", \")) + \"]<|tool_call_end|>\" -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(system_prompt=\"\", last_assistant_index=-1) -%}\n{%- if messages[0].role == \"system\" -%}\n {%- if messages[0].content is defined -%}\n {%- set ns.system_prompt = parse_content(messages[0].content) -%}\n {%- endif -%}\n {%- set messages = messages[1:] -%}\n{%- endif -%}\n{%- if tools -%}\n {%- set ns.system_prompt = ns.system_prompt + (\"\\n\\n\" if ns.system_prompt else \"\") + \"Today's date: \" + strftime_now(\"%Y-%m-%d\") + \"\\n\\nList of tools: \" + (tools | tojson) -%}\n{%- endif -%}\n{%- if ns.system_prompt -%}\n {{- \"<|im_start|>system\\n\" + ns.system_prompt + \"<|im_end|>\\n\" -}}\n{%- endif -%}\n{%- for message in messages -%}\n {%- if message.role == \"assistant\" -%}\n {%- set ns.last_assistant_index = loop.index0 -%}\n {%- endif -%}\n{%- endfor -%}\n{%- for message in messages -%}\n {{- \"<|im_start|>\" + message.role + \"\\n\" -}}\n {%- if message.role == \"assistant\" -%}\n \n {%- if message.thinking is defined and (keep_past_thinking or loop.index0 == ns.last_assistant_index) -%}\n {{- \"<think>\" + message.thinking + \"</think>\" -}}\n {%- endif -%}\n {%- if message.tool_calls is defined -%}\n {{- render_tool_calls(message.tool_calls) -}}\n {%- endif -%}\n {%- if message.content is defined -%}\n {%- set content = parse_content(message.content) -%}\n {%- if not keep_past_thinking and loop.index0 != ns.last_assistant_index -%}\n {%- if \"</think>\" in content -%}\n {%- set content = content.split(\"</think>\")[-1] | trim -%}\n {%- endif -%}\n {%- endif -%}\n {{- content + (\"\" if (continue_final_message and loop.last) else \"<|im_end|>\\n\") -}}\n {%- endif -%}\n \n {%- else %}\n {%- if message.content is defined -%}\n {{- parse_content(message.content) + \"<|im_end|>\\n\" -}}\n {%- endif -%}\n {%- endif %}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{- \"<|im_start|>assistant\\n\" -}}\n{%- endif -%}"
} |