base_model: openbmb/MiniCPM-V-2_6
datasets:
- openbmb/RLAIF-V-Dataset
language:
- multilingual
library_name: transformers
pipeline_tag: image-text-to-text
tags:
- minicpm-v
- vision
- ocr
- multi-image
- video
- custom_code
lm_studio:
param_count: 8b
use_case: image
release_date: 05-08-2024
model_creator: OpenBMB
prompt_template: ChatML
system_prompt: You are a helpful assistant.
base_model: MiniCPM-V
original_repo: openbmb/MiniCPM-V-2_6
💫 Community Model> MiniCPM-V 2.6 by OpenBMB
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Model creator: OpenBMB
Original model: MiniCPM-V-2_6
GGUF quantization: provided by bartowski based on llama.cpp release b3600
- Requires LM Studio version 0.3.0 and up, please check for updates
Model Summary:
MiniCPM-V 2.6 is the latest and most capable model in the MiniCPM-V series. The model is built on SigLip-400M and Qwen2-7B with a total of 8B parameters.
It exhibits a significant performance improvement over MiniCPM-Llama3-V 2.5, and introduces new features for multi-image and video understanding.
Prompt Template:
Choose the ChatML preset in your LM Studio.
Under the hood, the model will see a prompt that's formatted like so:
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Technical Details
MiniCPM-V 2.6 manages to beat widely used proprietary models like GPT-4o mini, GPT-4V, Gemini 1.5 Pro, and Claude 3.5 Sonnet for single image understanding.
MiniCPM-V 2.6 is capable of performing conversation and reasoning over multiple images, and is also able to accept video inputs
This model can process images with any aspect ratio and up to 1.8 million pixels (e.g., 1344x1344) and perform state of the art OCR on them.
Special thanks
🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.
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