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Kiterlin
GitHub-Creator-Profil

Kiterlin

Repository-Ansicht von 84 gesammelten Skills in 2 GitHub-Repositories.

gesammelte Skills
84
Repositories
2
aktualisiert
2. Sept. 2026
Repository-Explorer

Repositories und repräsentative Skills

ml-paper-writing
Technische Redakteure

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and…

9. Feb. 2026
huggingface-accelerate
Datenwissenschaftler

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace…

9. Feb. 2026
audiocraft-audio-generation
Softwareentwickler

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.

9. Feb. 2026
autogpt-agents
Softwareentwickler

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

9. Feb. 2026
awq-quantization
Softwareentwickler

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for…

9. Feb. 2026
axolotl
Datenwissenschaftler

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

9. Feb. 2026
evaluating-code-models
Softwarequalitätssicherungsanalysten und -tester

Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard…

9. Feb. 2026
quantizing-models-bitsandbytes
Softwareentwickler

Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with…

9. Feb. 2026
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