Discover the Best AI Resources
Curated essentials, no noise — just what matters
Multilingual on-device translation model compressed to 1.25-bit via the Sherry quantization, supporting 33 languages and 1,056 directions in a 440MB package for offline mobile translation and demos.
Collection of 76 image-centric multimodal subdatasets (≈6.9M samples, ~39.56B estimated tokens) for training vision–language models, each published with a standardized conversation JSONL and dataset card. Media are referenced by path/URL and must be fetched separately; licensing is primarily CC-BY-4.0 with per-subdataset variations.
Terminal-native AI coding assistant optimized for the deepseek-v4 model. Provides configurable "thinking" modes and reasoning-intensity controls, agent skills for extensibility, MCP integration, and a shared config with a VSCode plugin.
Parallel Khasi–English sentence pairs for machine translation research focused on low-resource NLP in Northeast India. Provided as a small CSV (sentence_id, english_text, khasi_text) under CC BY‑NC 4.0 for non-commercial research use.
Provides 104.9M curated image–text pairs with precomputed embeddings, structured annotations and pre-encoded VAE latents for text-to-image pretraining and retrieval. Combines filtered web sources and synthetic samples with multi-model re-captioning, deduplication and safety filters; Apache-2.0.
Provides reusable Docker compose files, scripts and benchmarked configs to serve modern LLMs (Qwen, Gemma, etc.) on 1–2 NVIDIA RTX 3090/4090/5090 GPUs. Multi-engine (vLLM, llama.cpp, ik_llama), measured TPS/context tradeoffs, and validated single/dual‑GPU recipes.
Converts latent representations into high-resolution images by using a conditional pixel-space diffusion decoder that merges decoding and upsampling into a single generative step. Released checkpoints are 4-step distilled (2k and 2kto4k variants) and pair with specific VAE/encoder weights; license restricts use to non-commercial research.
Large-scale synthetic video dataset of 236,937 1080p clips (≈5,841 hours) of digital humans with per-frame metric depth and camera parameters — built as a controllable supplement for world-model pretraining, camera-motion generalization, and geometry-aware physical-AI research.
An instruct-focused LLM (104B total, 7.4B active) optimized for fast, token-efficient inference in agent workflows. Uses hybrid linear attention plus a sparse MoE to raise throughput and cut token use; suited for high-frequency production agents, with some trade-offs in very deep reasoning.
Curated monolingual Khasi sentence corpus (CSV) with under 1,000 sentences for language modeling, tokenization, and low-resource NLP experiments. Single-column structure (khasi_sentence) and CC BY‑NC 4.0 license — suitable for research and data-augmentation workflows, not for commercial use.
Self-hosted sales CRM that runs native AI agents (RAG per tenant) to handle WhatsApp conversations, qualify leads, trigger automations and move deals through configurable pipelines. Multi-tenant with LGPD-minded controls and a one-command VPS installer for full data ownership.
Contains ~1,973 distilled roleplay conversations with character-perspective chain-of-thought traces (<think> blocks) for fine-tuning persona-focused chat models. Includes teacher provenance, safety/review flags, and filters for NSFW/borderline samples — suited for SFT and character retention tests.