cnb.cEr0mSxFAFA
a88c47e273
- 用 CharTokenizer.build_vocab 从 977K 数据生成词表 (vocab_size=47725) - train_cnb.py: batch=224 + accum=2 (等效448) + AMP + torch.compile - build_vocab.py: 词表生成脚本 - vocab_full.json: 含特殊token完整词表 - 模型 41.85M参数, L40 GPU训练
99 lines
3.3 KiB
Python
99 lines
3.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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API生成模块 — Astron 5并发，稳定不超限
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"""
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import json, requests, time, os, threading
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from concurrent.futures import ThreadPoolExecutor, as_completed
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ASTRON_URL = "https://maas-coding-api.cn-huabei-1.xf-yun.com/v2/chat/completions"
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ASTRON_KEY = os.environ.get("ASTRON_KEY", "")
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ASTRON_MODEL = "astron-code-latest"
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SYSTEM_PROMPT = """你是一个名叫小狸的8岁中国小女孩。
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你的人设：
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- 8岁女孩子，有点害羞但很可爱
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- 说话简单自然，符合小朋友的语气
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- 回答问题要简短，1-2句话就够了
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- 不要用"喵"结尾，不要过度卖萌
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回答要求：
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1. 语气自然，像真实的小朋友说话
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2. 不懂就说"不知道"
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3. 回答简洁但要说清楚，不要讲一半就停"""
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def call_astron(q, temperature=0.85):
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for attempt in range(3):
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try:
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headers = {"Content-Type": "application/json", "Authorization": f"Bearer {ASTRON_KEY}"}
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payload = {
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"model": ASTRON_MODEL,
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": q}
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],
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"temperature": temperature,
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"max_tokens": 8192,
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}
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resp = requests.post(ASTRON_URL, headers=headers, json=payload, timeout=60)
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if resp.status_code == 200:
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content = resp.json()['choices'][0]['message']['content'].strip()
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if content:
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return content
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else:
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time.sleep(1)
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except Exception:
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time.sleep(2)
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return None
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def batch_generate(questions, temperature=0.85, max_workers=4):
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"""Astron 4并发 — 明确限制，稳定可靠"""
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total = len(questions)
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results = []
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def call(q):
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ans = call_astron(q, temperature)
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if ans:
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return q, ans
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return None
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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futures = {executor.submit(call, item): i for i, item in enumerate(questions)}
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done = 0
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t0 = time.time()
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for f in as_completed(futures):
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done += 1
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r = f.result()
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if r:
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results.append({"question": r[0], "answer": r[1]})
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if done % 20 == 0 or done == total:
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elapsed = max(time.time() - t0, 1)
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rate = len(results) / elapsed * 60
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print(f" Astron: {done}/{total} (已获{len(results)}条, {rate:.0f}条/分)", end="\r")
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elapsed = time.time() - t0
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rate = len(results) / max(elapsed, 1) * 60
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print(f" Astron: {total}/{total} → 共{len(results)}条 ({elapsed:.0f}s, {rate:.0f}条/分)")
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return results
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# 保持旧函数名兼容
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batch_generate_astron = batch_generate
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batch_generate_mimo = batch_generate
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batch_generate_direct = batch_generate
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batch_generate_dual = batch_generate
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def batch_convert(items, *args, **kwargs):
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"""兼容占位：训练脚本导入用，已弃用"""
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print(" [API] batch_convert已弃用，使用batch_generate")
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return []
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def batch_generate_multi_temp(questions, *args, **kwargs):
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"""兼容占位：训练脚本导入用，已弃用"""
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print(" [API] batch_generate_multi_temp已弃用，使用batch_generate")
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return [] |