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Machine Learning

Training models and neural networks.

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machine-learning
403

apple-on-device-ai

Integrate on-device AI using Foundation Models framework, Core ML, and open-source LLM runtimes on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM). Use when building tool-calling AI features, working with guided generation schemas, converting models, or running on-device inference.

dpearson2699
dpearson2699
data-ai
open
machine-learning
403

coreml

Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.

dpearson2699
dpearson2699
data-ai
open
machine-learning
397

concave

Skill: concave

udecode
udecode
data-ai
open
machine-learning
397

convex

Skill: convex

udecode
udecode
data-ai
open
machine-learning
397

thesis-markdown-aligner

在 Markdown 中间层统一毕业论文的主线、术语、符号、指标、图表口径与章节边界，让整篇论文先在中间层收敛成“一篇论文”。 **Trigger**: markdown 对齐, thesis markdown align, 术语统一, 符号统一, 指标统一, 章节归并. **Use when**: 各章已经初步重构，但整篇论文仍有术语漂移、指标口径不一致、章节边界混乱或像多篇 paper 拼接。 **Skip if**: 章节角色还没定，或当前只是在局部修一章。 **Network**: none. **Guardrail**: 不在这里回写 tex；先收敛中间层，再进入交付层。

WILLOSCAR
WILLOSCAR
data-ai
open
machine-learning
393

nf-core-pipelines-skills-index

Skills for using nf-core community pipelines to process omics data, from installation and configuration to running specific analysis pipelines.

aristoteleo
aristoteleo
data-ai
open
machine-learning
378

swift-mlx-lm

MLX Swift LM - Run LLMs and VLMs on Apple Silicon using MLX. Covers local inference, streaming, wired memory coordination, tool calling, LoRA fine-tuning, embeddings, and model porting.

ml-explore
ml-explore
data-ai
open
machine-learning
377

aliyun-qwen-tts-voice-clone

Use when cloning voices with Alibaba Cloud Model Studio Qwen TTS VC models. Use when creating cloned voices from sample audio and synthesizing text with cloned timbre.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-tts-voice-design

Use when designing custom voices with Alibaba Cloud Model Studio Qwen TTS VD models. Use when creating custom synthetic voices from text descriptions and using them for speech synthesis.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-image

Use when generating images with Model Studio DashScope SDK using Qwen Image generation models (qwen-image, qwen-image-plus, qwen-image-max, qwen-image-2.0 series and snapshots). Use when implementing or documenting image.generate requests/responses, mapping prompt/negative_prompt/size/seed/reference_image, or integrating image generation into the video-agent pipeline.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-modelstudio-crawl-and-skill

Use when refreshing the Model Studio models crawl and regenerate derived summaries and `skills/ai/**` skills. Use when the models list or generated skills must be updated.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qvq

Use when visual reasoning is needed with Alibaba Cloud Model Studio QVQ models, including step-by-step image reasoning, chart analysis, and visually grounded problem solving.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-ocr

Use when OCR-specialized extraction is needed with Alibaba Cloud Model Studio Qwen OCR models (`qwen-vl-ocr`, `qwen-vl-ocr-latest`, and snapshots), including document parsing, table parsing, multilingual OCR, formula recognition, and key information extraction.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-omni

Use when tasks require all-in-one multimodal understanding or generation with Alibaba Cloud Model Studio Qwen Omni models, including image-plus-audio interaction, voice assistants, and realtime multimodal agents.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-vl

Use when understanding images with Alibaba Cloud Model Studio Qwen VL models (qwen3-vl-plus/qwen3-vl-flash and latest aliases). Use when building image Q&A, visual analysis, OCR-like extraction, chart/table reading, or screenshot understanding workflows.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-deep-research

Use when a task needs Alibaba Cloud Model Studio Qwen Deep Research models to plan multi-step investigation, run iterative web research, and produce structured reports with citations or evidence summaries.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-multimodal-embedding

Use when multimodal embeddings are needed from Alibaba Cloud Model Studio models such as `qwen3-vl-embedding` for image, video, and text retrieval, cross-modal search, clustering, or offline vectorization pipelines.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-rerank

Use when reranking search candidates is needed with Alibaba Cloud Model Studio rerank models, including hybrid retrieval, top-k refinement, and multilingual relevance sorting.

cinience
cinience
data-ai
open
machine-learning
377

aliyun-qwen-text-embedding

Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vectorization pipelines.

cinience
cinience
data-ai
open
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