heartmula
49Skill Claude CodeCodex
Set up and run HeartMuLa, the open-source music generation model family (Suno-like). Generates full songs from lyrics + tags with multilingual support.
not rated 178 3mo ago A 34 tokens
178Stars on the repository
100Mods indexed here, across every type
3mo agoLast push, which is what freshness is scored on
noneNo LICENSE: all rights reserved, so bodies are not copied
songsee
50Skill Claude CodeCodex
Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.
not rated 178 3mo ago A 45 tokens
Skill Claude CodeCodex
Fetch YouTube video transcripts and transform them into structured content (chapters, summaries, threads, blog posts).
not rated 178 3mo ago A 25 tokens
Skill Claude CodeCodex
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
not rated 178 3mo ago A 42 tokens
Skill Claude CodeCodex
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
not rated 178 3mo ago A 85 tokens
Skill Claude CodeCodex
Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform.
not rated 178 3mo ago A 39 tokens
Skill Claude CodeCodex
Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
not rated 178 3mo ago C 43 tokens
Skill Claude CodeCodex
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
not rated 178 3mo ago A 48 tokens
guidance
57Skill Claude CodeCodex
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework.
not rated 178 3mo ago A 38 tokens
llama-cpp
58Skill Claude CodeCodex
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
not rated 178 3mo ago A 76 tokens
obliteratus
59Skill Claude CodeCodex
Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets across 5 compute tiers, tournament…
not rated 178 3mo ago A 103 tokens
outlines
60Skill Claude CodeCodex
Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library.
not rated 178 3mo ago B 50 tokens
Skill Claude CodeCodex
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
not rated 178 3mo ago A 75 tokens
Skill Claude CodeCodex
PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.
not rated 178 3mo ago A 54 tokens
clip
63Skill Claude CodeCodex
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.
not rated 178 3mo ago A 60 tokens
Skill Claude CodeCodex
Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
not rated 178 3mo ago A 45 tokens
Skill Claude CodeCodex
State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.
not rated 178 3mo ago A 50 tokens
whisper
66Skill Claude CodeCodex
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual…
not rated 178 3mo ago B 67 tokens
dspy
67Skill Claude CodeCodex
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming.
not rated 178 3mo ago A 35 tokens
axolotl
68Skill Claude CodeCodex
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support.
not rated 178 3mo ago A 47 tokens
Skill Claude CodeCodex
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training.
not rated 178 3mo ago A 26 tokens
Skill Claude CodeCodex
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
not rated 178 3mo ago A 82 tokens
pytorch-fsdp
71Skill Claude CodeCodex
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2.
not rated 178 3mo ago B 37 tokens
Skill Claude CodeCodex
Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
not rated 178 3mo ago A 69 tokens
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