InternVL2_5-78B

Advanced multimodal large language model series

CommonProductImageMultimodalLarge Language Model

InternVL 2.5 is a series of advanced multimodal large language models (MLLM) that has evolved from InternVL 2.0, enhanced through significant training and testing strategy improvements as well as better data quality. This model series is optimized for visual perception and multimodal capabilities, supporting various functionalities, including transforming images and texts, making it suitable for complex tasks that involve visual and linguistic information.

Supports dynamic high-resolution training methods for multimodal data
enhancing the model's ability to process multiple image and video datasets.
Utilizes the 'ViT-MLP-LLM' architecture integrating the newly pretrained InternViT with various large language models.
Achieves effective integration of visual encoders and language models through a randomly initialized MLP projector.
Introduces a progressive expansion strategy to optimize the alignment between visual encoders and large language models.
Implements random JPEG compression and loss reweighting techniques to improve the model's robustness to noisy images and balance NTP loss for different response lengths.
Supports multiple image and video data inputs
broadening the application range of the model in multimodal tasks.

The target audience includes researchers
developers
and enterprise users
particularly those involved in AI applications that process visual and linguistic data. InternVL2_5-78B
with its robust multimodal processing capabilities and efficient training strategies

Using InternVL2_5-78B for image caption generation
transforming image content into textual descriptions.
In multi-image understanding tasks
employing InternVL2_5-78B to analyze and compare similarities and differences between various images.
In the video understanding domain

1. Visit the Hugging Face website and search for the InternVL2_5-78B model.
2. Download and load the model according to your application needs.
3. Prepare the input data
including images and text
and perform appropriate preprocessing.

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Monthly Visits

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Bounce Rate

46.04%

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5.2

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00:04:57

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InternVL2_5-78B Alternatives

InternVL 2.5 — Open-source multimodal large language model series

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InternVL2_5-1B — A large multimodal language model that supports image and text understanding.

Image•Multimodal•Large Language Model

InternVL2_5-4B — A multimodal large language model that integrates visual and language understanding.

Image•Multimodal•Large Language Model

InternVL2_5-2B — A multimodal large language model that supports deep interaction between images and text.

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InternVL2_5-8B — A multimodal large language model supporting interaction understanding between images and text.

Image•Multimodal•Large Language Model

InternVL2_5-26B — A large multimodal language model that integrates visual and linguistic understanding.

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InternVL2_5-78B

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InternVL2_5-78B Alternatives

InternVL 2.5 — Open-source multimodal large language model series

InternVL2_5-1B — A large multimodal language model that supports image and text understanding.

InternVL2_5-4B — A multimodal large language model that integrates visual and language understanding.

InternVL2_5-2B — A multimodal large language model that supports deep interaction between images and text.

InternVL2_5-8B — A multimodal large language model supporting interaction understanding between images and text.

InternVL2_5-26B — A large multimodal language model that integrates visual and linguistic understanding.

Amazon Nova — Amazon Nova is Amazon's next-generation foundational model, offering cutting-edge intelligence and industry-leading cost-effectiveness.

Pixtral-Large-Instruct-2411 — A 124B-parameter multimodal large language model.

DataChain — A modern Python data frame library designed specifically for artificial intelligence.

Aquila-VL-2B-llava-qwen — A visual-language model that intelligently processes both image and text information.

Ferret-UI-Llama8b — A multimodal large language model based on Llama-3-8B, focused on UI tasks.

UniMuMo — Unified model for text, music, and motion generation.

NVLM 1.0 — Cutting-edge multimodal large language model

Molmo — Advanced Multimodal AI Model Family

Llama-3.2-11B-Vision — A multimodal large language model that supports image and text processing.

Llama-3.2-3B — Multilingual Large Language Model

Pixtral 12B — The first multimodal Mistral model, supporting hybrid task processing for images and text.

pixtral-12b-240910 — A multimodal large language model that supports understanding of both images and text.

West Lake AI Model — A multimodal model with high emotional and intellectual intelligence

Reflection Llama-3.1 70B — The world's leading open-source large language model

OLMoE-1B-7B — An efficient open-source large language model.

mPLUG-Owl3 — A multimodal large language model that understands long image sequences.

Phi-3.5-vision — An advanced multimodal model that supports image and text understanding.

MedTrinity-25M — A large-scale multimodal medical dataset

lmms-finetune — A unified codebase for fine-tuning large multimodal models.

OmAgent — A multimodal intelligent agent framework for tackling complex tasks

Index-1.9B — Index-1.9B is a lightweight, open-source large language model developed independently by Bilibili.

Omost — Transforms the encoding capabilities of large language models into image generation capabilities.

EasyEdit — User-friendly framework for knowledge editing of large language models (LLMs)