Plugins
1 pluginResults for “r-multiple”
12 skills
antigravity Julia Pro
Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.
42.4k
nvidia Tao Run Automl
Run automated hyperparameter optimization for NVIDIA TAO models using AutoMLRunner, supporting multiple search algorithms and experiment tracking.
2.2k · bundle
orchestra-research Skypilot Multi Cloud Orchestration
Run ML training and batch jobs across multiple clouds with automatic cost optimization, spot instance recovery, and unified orchestration.
10.4k · bundle
More results
nvidia Tao Train Image Classification
Train, evaluate, distill, quantize, export, and run inference for PyTorch-based TAO image classification models with support for multiple backbones.
2.2k · bundle
orchestra-research Speculative Decoding
Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques for 1.5-3.6× speedup without quality loss.
10.4k · bundle
orchestra-research Openrlhf Training
Train large language models (7B-70B+) with RLHF using PPO, GRPO, DPO, and other algorithms, accelerated by Ray and vLLM for distributed multi-GPU setups.
10.4k · bundle
orchestra-research Verl Rl Training
Train LLMs with reinforcement learning using verl (Volcano Engine RL), supporting RLHF, GRPO, PPO, and other algorithms for scalable post-training with flexible infrastructure backends.
10.4k · bundle
orchestra-research Rwkv Architecture
Use RWKV, a linear-time RNN-Transformer hybrid, for efficient long-context inference and training with constant memory usage.
10.4k · bundle
schattenspiegel Numpyro Python
Write, debug, and test NumPyro probabilistic programs on JAX with correct shapes, PRNG keys, and inference choice.
0 · bundle
orchestra-research Model Merging
Merge multiple fine-tuned models using mergekit to combine capabilities without retraining, covering SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.
10.4k · bundle
orchestra-research Hqq Quantization
Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends for deployment with vLLM or HuggingFace Transformers.
10.4k · bundle
qhjqhj00 Bbh Eval
Benchmarks zero-shot in-context learning on BIG-Bench Hard multiple-choice tasks, comparing self-generated demonstrations against direct prompting and chain-of-thought baselines, and reports accuracy.
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