Qwen · Model hubs and datasets

Complete agent-ready workflow for Qwen-family MTP or nextn GGUF conversion and release.

R6410418/Jackrong-llm-finetuning-guide

A skill your agent uses when adding support for a new model to VeOmni.

ByteDance-Seed/VeOmni

Adapt and port new LLM model architectures to this xinfer project.

guoqingbao/xinfer

Always resolve Hugging Face models via model-shelf before any download.

alexziskind1/model-shelf

Check model compatibility with xinfer before loading. An agent skill from guoqingbao/xinfer.

guoqingbao/xinfer

Test LLM models served by xinfer for correctness, output quality, and performance.

guoqingbao/xinfer

Draw Sebastian-Raschka-gallery-style TikZ architecture diagrams for any HuggingFace decoder-only LLM, with per-block parameter formulas and concrete numbers.

yzlnew/infra-skills

Builds and publishes a Gradio demo on Hugging Face Spaces for a LoRA, with the pipeline, UI and settings chosen to match that LoRA's task and model card.

huggingface/skills

Estimate GPU memory usage for Megatron-based MoE (Mixture of Experts) and dense models.

yzlnew/infra-skills

Set up the minimal set of artifacts (tokenized DCLM corpus shard + released HuggingFace checkpoint converted to DCP) required to benchmark, profile, or regression-test a MoE model in PithTrain.

mlc-ai/pith-train

Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA.

sickn33/agentic-awesome-skills

Validate workspace shape, model paths, output directories, and repo structure before downstream Quark skills proceed.

amd/Quark

Runs an end-to-end AMD Quark post-training quantization workflow for PyTorch / Hugging Face LLMs: inspect a Hub or local model, choose a quantization plan, create reproducible artifacts, request…

amd/Quark

Migrate any HuggingFace model to Ascend NPU torchair graph mode (torch.compile) and benchmark it for accuracy and performance against NPU eager and CPU eager.

ascend-ai-coding/awesome-ascend-skills