Structured, downloadable JSONL dataset of Seedance 2.0 video-generation prompts with matching MP4 previews and cover images; includes English/Chinese texts and standardized metadata (duration, resolution, safety) and is released under CC BY 4.0 for reuse.
A prompt-only mixture of ~478k prompts designed to support antidoom-style generation and preference-data pipelines for reducing model repetition (doom loops). Prompts are stripped of answers and labels and sourced from many public datasets so it’s usable for FTPO/adapter generation but not for supervised QA evaluation.
Provides 19,331 multi-turn ChatML Hermes reasoning traces produced by DeepSeek V4 Pro for LoRA fine-tuning of agent-style models; includes VRAM-tiered variants, train/valid/test splits, and dense tool-calling annotations in Parquet format.
Provides 19,331 multi-turn ChatML Hermes reasoning traces for LoRA fine-tuning of local models to behave as Hermes agents. Includes train/valid/test splits, VRAM-tiered variants (nano→spark), ~138K tool-call annotations, and Parquet format under Apache-2.0.
Agentic coding evaluation dataset containing real-world, multi-step developer tasks and raw model responses across 20+ programming languages. Emphasizes challenging, persona-driven prompts for benchmarking and fine-tuning; users should filter and audit outputs before training.
Trains reusable natural-language 'skills' for frozen LLM agents by optimizing the skill document in text-space — using trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts. Multi-backend, zero inference-time cost at deployment, designed for iterative, validation-led skill improvement.
Generates and edits high-resolution images (up to 2048×2048) from text and reference images, plus subject-driven personalization. Implements a pixel-level unified transformer that encodes raw pixels and text in one token space and includes a reasoning-driven prompt agent for layout and text rendering.
Provides a locally runnable 26.9B Qwen3.6 checkpoint that surgically reduces refusal behavior in weight space while preserving capability; ships bfloat16 safetensors and a GGUF quant ladder for local runtimes and red-team evaluation.
Supervised fine-tuning dataset of instruction-style examples in English and Chinese covering generation, QA, reasoning, math and code — targeted for SFT of 10–100B-parameter LLMs. Associated with arXiv:2602.09003; first published May 21, 2026.
Spawns parallel, isolated LLM reasoning frames, then scores, clusters and prunes ideas to avoid premature convergence. Packaged as a reusable Claude/Codex agent skill with CLI and TypeScript APIs for ideation, design decisions and fuzzy debugging.
Provides ~3.8M chain-of-thought training examples (~3B tokens) that use a fixed 'Inventory / Interaction / Execution' scaffold to improve concise, reliable reasoning in small LLMs; topic-labeled, deduped, includes real tool-execution traces, CC-BY-4.0.
Encodes and clones camera motion from reference videos to generate multi-shot videos — uses a visual "camera grid" to represent camera parameters, trains on million-scale grid–video pairs, and employs a hierarchical prompt-expansion agent to coordinate camera, subject, and action control for multimodal diffusion models.