ascend-ai-coding/awesome-ascend-skills - Page 6

mindspeed-mm-generative

Universal MindSpeed-MM generative model training guide for Huawei Ascend NPU. Covers all backend patterns (Megatron, Megatron+FSDP2, FSDP2-native, Accelerate+DeepSpeed), feature extraction, weight conversion, and training for ALL supported generative models.…

Langue du texte source : anglais

mindspeed-mm-pipeline

MindSpeed-MM skill router and model index for Huawei Ascend NPU. Use when the user is uncertain which MindSpeed-MM skill to use, needs to choose between understanding/generative/omni/audio model categories, or wants an overview of the full training pipeline.…

Langue du texte source : anglais

mindspeed-mm-vlm

Universal VLM (vision-language understanding model) training guide for Huawei Ascend NPU using MindSpeed-MM. Covers all three framework patterns (Megatron, FSDP2, Custom trainers), weight conversion, dataset preparation (MLLM JSON format), fine-tuning,…

Langue du texte source : anglais

mindspeed-mm-weight-prep

MindSpeed-MM weight conversion guide using mm-convert CLI tool. Covers HuggingFace to MindSpeed-MM format conversion, reverse conversion, and PP weight resplitting. Supports Qwen2VLConverter, Qwen2_5_VLConverter, InternVLConverter, WanConverter and more. Use…

Langue du texte source : anglais

torch-npu-comm-test

通过 PyTorch torch.distributed 接口测试昇腾 NPU 通信算子性能。支持指定任意 tensor shape、dtype，使用 torchrun 启动，贴近真实训练场景的通信算子测试与性能分析。Use for testing collective communication operators (AllReduce, AllGather, ReduceScatter, etc.) with specific tensor shapes via torch.distributed on…

Langue du texte source : chinois

verl-quickstart

Generates an executable, end-to-end VERL reinforcement learning quickstart runbook for Ascend/NPU (docker image, dataset preprocessing, model setup, main_ppo training, and examples/run_*.sh flow). Use when users mention verl, quickstart, PPO/GRPO, gsm8k,…

Langue du texte source : chinois

create-pr

Creates GitHub pull requests with properly formatted titles that pass the check-pr-title CI validation. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request.

Langue du texte source : anglais