jayll1303/AIEKit

jayll1303/AIEKit

Skill

Analyze project and recommend relevant AIE-Skills. Use when installing, setting up ML skills, bootstrapping AI/ML workflow, or sharing skills across repos.

jayll1303/AIEKit

Skill

Read and analyze arXiv papers via HTML. Use when user mentions arxiv, paper, research paper, academic paper, arxiv ID, or asks to read/summarize/analyze a scientific paper.

jayll1303/AIEKit

Skill

Diagnose and clean disk space on Linux servers, especially ML/LLM servers with Docker. Use when disk full, df shows high usage, du mismatch, Docker eating space, deleted files still consuming space, or need to free up disk on EC2/GPU server.

jayll1303/AIEKit

Skill

Build reproducible GPU-enabled Docker containers for ML/CUDA workloads. Use when writing GPU Dockerfiles, selecting NGC base images, configuring docker-compose GPU passthrough, setting up NVIDIA Container Toolkit, or installing uv inside Docker containers.

jayll1303/AIEKit

Skill

Set up selfhosted experiment tracking with MLflow or W&B. Use when deploying MLflow servers, configuring W&B selfhosted, logging metrics and artifacts, comparing experiment runs, managing model registry, or troubleshooting offline sync.

jayll1303/AIEKit

Skill

Build production-grade FastAPI at scale. Use when structuring projects, async SQLAlchemy, Alembic migrations, JWT auth, rate limiting, testing with httpx, deploying uvicorn/gunicorn/Docker.

jayll1303/AIEKit

Skill

Develop crypto trading strategies with Freqtrade. Use when creating IStrategy classes, writing populateindicators/entry/exit, running backtesting/hyperopt, configuring bot JSON, implementing callbacks (customstoploss, DCA, leverage), or downloading OHLCV data.

jayll1303/AIEKit

Skill

Download, upload, and stream HuggingFace models and datasets. Use when downloading pretrained models with snapshotdownload, loading datasets with loaddataset, pushing to Hub with pushtohub, streaming large datasets, or managing private repos and gated models.

jayll1303/AIEKit

Skill

Best practices and architecture patterns for huggingface/speech-to-speech queue-chained pipeline. Use when building speech-to-speech pipelines, adding STT/LLM/TTS handlers, wiring queue-based audio processing stages, implementing VAD with progressive streaming, or designing real-time voice agent architectures.

jayll1303/AIEKit

Skill

Fine-tune and align LLMs locally with HuggingFace Trainer, TRL, PEFT. Use when configuring TrainingArguments, applying LoRA or QLoRA, running SFT/DPO/GRPO alignment, estimating VRAM requirements, debugging OOM errors, or setting up gradient checkpointing.

jayll1303/AIEKit

Skill

Train speech models with Next-gen Kaldi ecosystem: k2 (FSA/FST loss), icefall (Zipformer/Conformer recipes), lhotse (data prep). Use when training ASR/TTS models, preparing speech datasets, exporting to ONNX for sherpa-onnx, or fine-tuning pre-trained speech models.

jayll1303/AIEKit

Skill

Run GGUF models locally with llama.cpp. Use when launching llama-server, running llama-cli, using llama-cpp-python, configuring GGUF inference on CPU+GPU, or tuning continuous batching.

jayll1303/AIEKit

Skill

Brainstorm ML/AI decisions: training strategy, model selection, serving engine, quantization, pipeline architecture. Use when comparing approaches, evaluating tradeoffs, or planning ML workflows.

jayll1303/AIEKit

Skill

Modal job orchestration with .map, .starmap, .spawn, .spawnmap, @modal.batched. Use when fanning out work, polling job IDs, capping concurrency, or batching GPU calls.

jayll1303/AIEKit

Skill

Use this skill for Modal Sandbox lifecycle and interactive isolated execution. Trigger when the user needs to run untrusted or user-supplied code in a sandbox, keep a long-lived controller process alive, stream stdout from exec() calls, reattach to an existing sandbox, upload files at runtime, expose a tunneled HTTP…

jayll1303/AIEKit

Skill

Quantize large language models to reduce VRAM and accelerate inference with GGUF, GPTQ, AWQ, bitsandbytes. Use when converting models to GGUF format, applying GPTQ/AWQ weight-only quantization, loading models in 4-bit or 8-bit with BitsAndBytesConfig, or comparing quantization methods for VRAM budget.

jayll1303/AIEKit

Skill

Create, edit, and manage Jupyter/Colab .ipynb notebooks programmatically. Use when creating notebooks, adding/editing cells, parsing notebook output, handling Colab features (GPU, Drive mount), or converting notebook formats.

jayll1303/AIEKit

Skill

Run and manage local LLMs with Ollama. Use when running ollama run, ollama pull, creating Modelfiles, serving local LLM APIs, using ollama serve, or integrating Ollama REST/OpenAI-compatible API.

jayll1303/AIEKit

Skill

Build OpenAI-compatible audio/speech APIs with FastAPI, dynamic batching, and streaming synthesis. Use when building TTS servers, audio inference APIs, or wrapping audio ML models behind HTTP.

jayll1303/AIEKit

Skill

Instrument apps with OpenTelemetry for distributed tracing, metrics, and logs. Use when setting up OTel SDK, auto-instrumenting Python/Node.js, configuring Collector pipelines, or choosing sampling.

jayll1303/AIEKit

Skill

OCR with PaddlePaddle: PaddleOCR text detection, recognition, fine-tuning, dataset prep, PP-OCRv5, PP-StructureV3. Use when training OCR models, preparing OCR datasets, fine-tuning detection/recognition, exporting PaddleOCR inference models, or deploying OCR pipelines.

jayll1303/AIEKit

Skill

Install ML/AI Python deps with uv, resolve NVIDIA version conflicts. Use when installing PyTorch with CUDA index URLs, building Flash-Attention from source, resolving CUDA/cuDNN/driver version conflicts, installing bitsandbytes, or configuring pyproject.toml with CUDA-specific extras.

jayll1303/AIEKit

Skill

Bootstrap and configure Python projects with uv, ruff, and pytest. Use when running uv init, setting up pyproject.toml, configuring ruff linting and formatting, configuring pytest, adding pre-commit hooks, or migrating from pip or Poetry.

jayll1303/AIEKit

Skill

Strengthen Python code quality and test suites. Use when adding type annotations, writing contract docstrings, auditing exception handling, implementing Hypothesis property-based testing, running mutmut mutation testing, or performing code quality reviews.