executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
architecture-and-loadingOperate Baichuan-7B architecture, local source loading, tiny synthetic forward checks, Hugging Face inference loading, and generation/cache preparation.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the user asks to load or inspect Baichuan-7B model code, reason about BaiChuanConfig defaults, construct BaiChuanForCausalLM, run a tiny local forward smoke, understand generate()/cache preparation, or debug attention/head shape constraints.
AutoTokenizer / AutoModelForCausalLM and trust_remote_code=True.BaiChuanConfig, Model, Attention, DecoderLayer, and BaiChuanForCausalLM.past_key_values, attention_mask, position_ids, use_cache, and newer Transformers generation warnings.hidden_size / num_attention_heads combinations or direct attention-mask shape errors.evaluation-workflows.pretraining-and-deepspeed.--repo-root /path/to/Baichuan-7B.python sub-skills/architecture-and-loading/scripts/local_model_smoke.py --repo-root /path/to/Baichuan-7B
Expected coverage: local source import, tiny BaiChuanConfig, eval-mode BaiChuanForCausalLM forward, logits shape (1, 4, 32), finite causal-LM loss, cache-aware prepare_inputs_for_generation, invalid head-divisibility failure, and has_generate reporting.
Add --cuda only when the user explicitly wants a CUDA availability/allocation check; it does not download or run the real 7B model.