JGZYES
28535b1c74
- pmai unified CLI (generate/chat/interactive/http/inspect/output/config) - GPT+MoE transformer, .pap (f32/fp16/q8) + GGUF loader (order+version adaptive) - llama/Mixtral arch: RoPE+GQA+SwiGLU+MoE (C==torch verified) - C llama BPE tokenizer (validated vs llama-cpp-python) - training framework + 0.1B/0.22B MoE models; quantization fp16/q8 - build artifacts to output/; HTTP API; config.yaml; scripts; openapi
42 行
1.3 KiB
Python
42 行
1.3 KiB
Python
# -*- coding: utf-8 -*-
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"""把自研 MoE 模型的 .pap 导出成标准 GGUF 容器。
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用法:
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/opt/pap-venv/bin/python platform/export_gguf.py \
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--src models/moe-0.1b.pap --dst models/moe-0.1b.gguf --dtype fp16 # 或 q8 / f32
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"""
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from __future__ import annotations
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import argparse
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import os
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import pap_format
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import gguf_format
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GML = {"f32": 0, "fp16": 1, "q8": 8}
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--src", required=True)
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ap.add_argument("--dst", required=True)
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ap.add_argument("--dtype", default="fp16", choices=GML.keys())
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args = ap.parse_args()
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cfg, vocab, merges, tensors = pap_format.read_pap(args.src)
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gguf_format.save_gguf(args.dst, cfg, vocab, merges, tensors, GML[args.dtype])
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in_sz = os.path.getsize(args.src)
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out_sz = os.path.getsize(args.dst)
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print(f"已导出: {args.src} ({in_sz/1e6:.1f} MB) -> {args.dst} ({out_sz/1e6:.1f} MB)")
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# 读回验证
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rt, meta, ver = gguf_format.read_gguf(args.dst)
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print(f"读回校验: version={ver} tensors={len(rt)} metadata={len(meta)}")
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print(f" general.architecture = {meta.get('general.architecture')}")
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print(f" pap.vocab_size = {meta.get('pap.vocab_size')} pap.moe_n_experts = {meta.get('pap.moe_n_experts')}")
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if __name__ == "__main__":
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main()
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