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name: architecture-and-loading description: "Operate Baichuan-7B architecture, local source loading, tiny synthetic forward checks, Hugging Face inference loading, and generation/cache preparation." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Architecture and Loading

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.

Route here for

• Loading Baichuan-7B or compatible local weights with Hugging Face AutoTokenizer / AutoModelForCausalLM and trust_remote_code=True.
• Inspecting the local classes BaiChuanConfig, Model, Attention, DecoderLayer, and BaiChuanForCausalLM.
• Running a safe config-only smoke that needs no official 7B weights, no datasets, and no network.
• Explaining generation preparation: past_key_values, attention_mask, position_ids, use_cache, and newer Transformers generation warnings.
• Diagnosing invalid hidden_size / num_attention_heads combinations or direct attention-mask shape errors.

Do not route here for

• C-Eval/MMLU benchmark data, scoring commands, or result files: use sibling evaluation-workflows.
• DeepSpeed pretraining, corpus shards, tokenizer placement for training, hostfiles, or cluster launch commands: use sibling pretraining-and-deepspeed.
• General package installation decisions that affect multiple workflows: start at the parent root skill and shared troubleshooting.

Operating map

1. For a quick answer, read workflows first.
2. For local source verification, run scripts/local_model_smoke.py with --repo-root /path/to/Baichuan-7B.
3. For known failures, read local troubleshooting, then escalate cross-cutting install/backend issues to shared troubleshooting.
4. For broader API placement, use the parent Baichuan-7B repo skill and shared API reference.

Minimal safe smoke

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.