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ECCV 2024 M3DBench introduces a comprehensive 3D instruction-following dataset with support for interleaved multi-modal prompts.
NeurIPS 2023 Datasets and Benchmarks Track LAMM: Multi-Modal Large Language Models and Applications as AI Agents
Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models
This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of large language models. It serves as a structured natural language processing resource, offering a collection of text data that includes dialogue, customer service interactions, and creative writing. The dataset is organized into distinct thematic categories, allowing for targeted model development across specific conversational and narrative contexts. By providing information in standardized, schema-agnostic text formats, the collection ensures portability across various machine l
A VQA dataset that includes unanswerable questions [TPAMI 2024].
The main features of guoyang9/unk-vqa are: Evaluation Benchmarks, Pre-training Datasets.
Projects with overlapping indexed features include: openm3d/m3dbench — [ECCV 2024] M3DBench introduces a comprehensive 3D instruction-following dataset with support for interleaved… hypjudy/sparkles — Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models. openlamm/lamm — [NeurIPS 2023 Datasets and Benchmarks Track] LAMM: Multi-Modal Large Language Models and Applications as AI Agents. plexpt/chatgpt-corpus — This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of… datawhalechina/prompt-engineering-for-developers — This project is a technical curriculum and development guide focused on large language model prompt engineering,… pyspur-dev/pyspur.