Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
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Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.
Run a 105 GB AI model on a Mac that can't hold it. Qwen3.8-Flash-Next 4-bit, streamed from SSD on 16–64 GB Apple Silicon Macs. Fully native Swift, MLX and Metal. Offline, no Python. CLI, Swift library, and Ollama/OpenAI/Anthropic APIs. Works with Claude Code and Codex.
Tamper-evident tracing, policy gates and cross-checks for AI agents: see what the agent did, and why.
🔥 The first-ever interactive streaming video generation benchmark.
Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.
TranslatedAI Paper System · AI paper generation, AI paper writing, one-click paper generation, AIGC rate reduction, plagiarism similarity reduction, thesis defense PPT · OEM white-label franchise recruitment
Build AI phone agents on your own computer and test every change with an AI caller. Open source, runs free with no API keys, cents per call with your own keys. Imports Dialogflow CX.
A comprehensive observability solution for monitoring Claude Code usage, performance, and costs.
Youtu-Parsing: Perception, Structuring and Recognition via High-Parallelism Decoding && Youtu-Parsing-Omni: One Encoder, One Schema, All Modalities
Xolotl: run DeepSeek-V4.1-Flash, all 552B, as a local coding agent on one gaming PC (RTX 4090 + 110 GB RAM): ~33 tok/s on agent tasks, ~41 in fast mode, 512K context. Plus GLM-5.3-Flash, Qwen3.8 and LFM3-Omni. MoE experts tiered across VRAM, pinned RAM and NVMe, with Xolotl Direct NVMe->VRAM. OpenAI + Anthropic API.
Your personal EQ coach. Build social skills and learn to handle conflict through realistic role-play and personalized feedback.
🧱 Experimental library for building inference engines
Translatedchat-keeper focuses on providing a Claude mirror site. It offers an experience that is a 1:1 recreation of the official website, and it can be accessed directly from within China.
Translated🔥🔥🔥Graduation thesis AI assistant, AI graduation thesis, graduation thesis writing, thesis proposal, literature review, AI paper generation, reducing AIGC rate, reducing similarity and plagiarism check rate, formatting and layout, defense PPT
Run models larger than your RAM or VRAM by streaming MoE experts from SSD. Built on llama.cpp.
A unified AI model hub for aggregation & distribution. It supports cross-converting various LLMs into OpenAI-compatible, Claude-compatible, or Gemini-compatible formats. A centralized gateway for personal and enterprise model management. 🍥
TranslatedThe operational superset of Pi Coding Agent — everything Pi, plus observability, governance, recovery, evaluation and multi-agent orchestration.
Run Claude Code natively on Android via Termux or AVF (Android Virtualization Framework) -- no desktop, no SSH, no root required.
OpenAI (and DeepSeek, Azure OpenAI, YandexGPT, Ollama, GigaChat, Qwen) API wrapper for Delphi. Use ChatGPT, DALL-E, Whisper and other products.
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.
C++/CUDA single-GPU inference engine for Qwen3.8 (incl. Qwen3.8-Flash-Next with offloaded experts) on the RTX 5090; grew from NInfer
A ChatGPT, Gemini, Claude, and Ollama(offline) plug-in for Embarcadero RAD Studio IDE XE5 to 12.1
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.