{ "bomFormat": "CycloneDX", "specVersion": "1.6", "serialNumber": "urn:uuid:0fd73414-9e65-47c5-8598-9745c0e73210", "version": 1, "metadata": { "timestamp": "2025-06-05T09:41:23.012895+00:00", "component": { "type": "machine-learning-model", "bom-ref": "OpenGVLab/InternVL-Chat-V1-5-c62ebeb8-2b6a-572f-945a-ebc349c329f4", "name": "OpenGVLab/InternVL-Chat-V1-5", "externalReferences": [ { "url": "https://huggingface.co/OpenGVLab/InternVL-Chat-V1-5", "type": "documentation" } ], "modelCard": { "modelParameters": { "task": "image-text-to-text", "architectureFamily": "internvl_chat", "modelArchitecture": "InternVLChatModel" }, "properties": [ { "name": "library_name", "value": "transformers" }, { "name": "base_model", "value": "OpenGVLab/InternViT-6B-448px-V1-5, internlm/internlm2-chat-20b" }, { "name": "base_model_relation", "value": "merge" } ] }, "authors": [ { "name": "OpenGVLab" } ], "licenses": [ { "license": { "id": "MIT", "url": "https://spdx.org/licenses/MIT.html" } } ], "description": "

\"Image

> _Two interns holding hands, symbolizing the integration of InternViT and InternLM._We introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding.We introduce three simple designs:1. **Strong Vision Encoder:** we explored a continuous learning strategy for the large-scale vision foundation model---InternViT-6B, boosting its visual understanding capabilities, and making it can be transferred and reused in different LLMs.2. **Dynamic High-Resolution:** we divide images into tiles ranging from 1 to 40 of 448 \u00d7 448 pixels according to the aspect ratio and resolution of the input images, which supports up to 4K resolution input during inference.3. **High-Quality Bilingual Dataset:** we carefully collected a high-quality bilingual dataset that covers common scenes, document images, and annotated them with English and Chinese question-answer pairs, significantly enhancing performance in OCR- and Chinese-related tasks.", "tags": [ "transformers", "tensorboard", "safetensors", "internvl_chat", "feature-extraction", "internvl", "custom_code", "image-text-to-text", "conversational", "multilingual", "arxiv:2312.14238", "arxiv:2404.16821", "arxiv:2410.16261", "arxiv:2412.05271", "base_model:OpenGVLab/InternViT-6B-448px-V1-5", "base_model:merge:OpenGVLab/InternViT-6B-448px-V1-5", "base_model:internlm/internlm2-chat-20b", "base_model:merge:internlm/internlm2-chat-20b", "license:mit", "region:us" ] } } }