Discover the Best AI Resources
Curated essentials, no noise — just what matters
AI Model2026
Transforms pretrained latent-diffusion priors into pixel-space diffusion models by removing the VAE and training shallow pixel layers on LDM-generated synthetic images — enabling fast convergence, native 4K output, and low-data training on 8 GPUs.
AI Dataset2026
Provides paired images and English captions for vision–language research, curated by Stanford Vision Lab and hosted on Hugging Face; useful for training and evaluating multimodal models and reproducing related research.
AI Dataset2026
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.
AI Dataset2026
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.
AI Model2026
Mixture-of-Experts LLM tuned for mathematical and coding reasoning, with ~760M active / 8.4B total parameters and post-training for improved stepwise reasoning. Optimized for inference efficiency (vLLM/transformers forks) so it can run in computation-constrained or local deployments; Apache-2.0 licensed.
AI Infra2026
Provides tools and samples to build context management, enrichment, and retrieval solutions on Google Cloud Knowledge Catalog — an AI-oriented data catalog that builds a dynamic knowledge graph for structured and unstructured data, suitable for RAG and agent workflows.
AI Infra2026
Defines OpenTelemetry semantic conventions for generative AI telemetry — spans, metrics, and events for GenAI clients, the Model Context Protocol (MCP), and provider-specific integrations. Includes YAML models, human-readable docs, and reference implementations to standardize observability across GenAI deployments.
AI Dataset2026
Large-scale synthetic video dataset of physically simulated multi-object interaction scenes for training and evaluating models on physical reasoning, depth and optical-flow estimation, instance segmentation, and physics-grounded captioning. Provides RGB + lossless depth, per-frame instance masks, per-object physics annotations (NPZ), VLM-grounded captions, and USD scene files — useful for world-model and simulation-to-real work; commercial use permitted.
AI Dataset2026
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.
AI Dataset2026
Provides a county-harmonized corpus of U.S. municipal and county ordinance text (≈2.21M chunks) labeled for function, substantive indicator, and topic to support legal NLP, retrieval, and comparative local-law research. Includes model-assigned labels and continuous scorers (opacity, paternalism, enforcement discretion) plus coverage metadata; not exhaustive or a substitute for legal advice.
AI Model2026
Merges Unsloth UD XL quantized GGUF of Qwen3.6-27B with compact Q8_0 MTP heads to enable multi-token (speculative) decoding on llama.cpp builds that support MTP; aimed at image-text-to-text usage with reduced MTP overhead.
AI Dataset2026
A retrieval benchmark suite focused on “oblique queries,” where relevance depends on latent attributes rather than surface keywords. Includes five tasks with large corpora, qrels (and pooled judgments), and task-specific constraints for evaluating embedding-based retrievers and reasoning-augmented retrieval.