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HYPJUDY avatar

HYPJUDY/Sparkles

0
View on GitHub↗
45 stars·1 fork·Python·BSD-3-Clause·3 views

Sparkles

Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models

Features

  • Evaluation Benchmarks - Unlocking multi-image chat and instruction following.
  • Multimodal Benchmarks - GPT-assisted benchmark for multi-image instruction following.
  • Pre-training Datasets - Machine-generated dialogue for multi-image instruction following.

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Frequently asked questions

What does hypjudy/sparkles do?

Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models

What are the main features of hypjudy/sparkles?

The main features of hypjudy/sparkles are: Evaluation Benchmarks, Multimodal Benchmarks, Pre-training Datasets.

What are some open-source alternatives to hypjudy/sparkles?

Open-source alternatives to hypjudy/sparkles include: openm3d/m3dbench — [ECCV 2024] M3DBench introduces a comprehensive 3D instruction-following dataset with support for interleaved… openlamm/lamm — [NeurIPS 2023 Datasets and Benchmarks Track] LAMM: Multi-Modal Large Language Models and Applications as AI Agents. fuxiaoliu/lrv-instruction — [ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning. ailab-cvc/seed-bench — (CVPR2024)A benchmark for evaluating Multimodal LLMs using multiple-choice questions. freedomintelligence/mllm-bench — MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria. bradyfu/video-mme — ✨✨[CVPR 2025] Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.