Merge branch 'pretrain' of http://110.42.53.85:3000/iomgaa/Minimind into pretrain
This commit is contained in:
Aurora
commit
6590cef358
@ -6,7 +6,6 @@ distributed_type: DEEPSPEED
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downcast_bf16: 'no'
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machine_rank: 0
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main_training_function: main
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mixed_precision: bf16
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num_machines: 1
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num_processes: 4
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rdzv_backend: static
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@ -17,12 +17,7 @@
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"contiguous_gradients": true
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},
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"fp16": {
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"enabled": "auto",
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"loss_scale": 0,
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||||
"loss_scale_window": 1000,
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||||
"initial_scale_power": 16,
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||||
"hysteresis": 2,
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"min_loss_scale": 1
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"enabled": false
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||||
},
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"bf16": {
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"enabled": true
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83
main.py
Normal file
83
main.py
Normal file
@ -0,0 +1,83 @@
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import logging
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import langextract as lx
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import os
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os.environ["LANGEXTRACT_API_KEY"] = "gpustack_d402860477878812_9ec494a501497d25b565987754f4db8c"
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# 可选：开启日志，便于调试
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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# 输入文本
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input_text = """
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这篇文章介绍了张华，他今年32岁，是一位经验丰富的工程师。
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他的同事李明，今年28岁，是一位充满活力的设计师。
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他们一起在一家科技公司工作。
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"""
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# 提取示例（用于 prompt alignment）
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examples = [
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lx.data.ExampleData(
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text="王小明，25岁，是一名软件开发者。",
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extractions=[
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lx.data.Extraction(
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extraction_class="person",
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extraction_text="王小明",
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attributes={"age": "25", "occupation": "软件开发者"}
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)
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]
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)
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]
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# HTTP API 配置（注意：不要带 /v1）
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# 创建ModelConfig，强制使用OpenAI提供者访问vllm端点
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model_config = lx.factory.ModelConfig(
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model_id="gpt-oss", # 使用vllm中实际部署的模型名称
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provider="OpenAILanguageModel", # 强制指定OpenAI提供者
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provider_kwargs={
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"base_url": "http://192.168.31.127:19090/v1", # vllm API端点
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"api_key": "gpustack_d402860477878812_9ec494a501497d25b565987754f4db8c",
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"model_id": "gpt-oss" # 确保使用正确的模型ID
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}
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)
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# LangExtract通用配置参数
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extract_config = {
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"config": model_config,
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"max_workers": 5, # 降低并发，避免过载vllm服务
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"max_char_buffer": 6000, # 适合医学论文的上下文长度
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"extraction_passes": 1, # 单次提取，避免过多API调用
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"temperature": 0.1, # 较低温度确保一致性
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"fence_output": True, # 期望代码围栏格式输出
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"use_schema_constraints": False, # vllm可能不支持严格schema
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"debug": False
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}
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try:
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result = lx.extract(
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text_or_documents=input_text,
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prompt_description="从文本中提取人物姓名、年龄等信息",
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examples=examples,
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**extract_config
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)
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# result = lx.extract(
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# text_or_documents=input_text,
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# prompt_description="从文本中提取人物姓名、年龄等信息",
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# examples=examples,
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# model_id="gpt-oss", # Automatically selects OpenAI provider
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# api_key="gpustack_d402860477878812_9ec494a501497d25b565987754f4db8c",
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# model_url="http://192.168.31.127:19090/v1",
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# fence_output=True,
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# use_schema_constraints=False
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# )
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# 输出结果
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print("提取结果：")
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for extraction in result.extractions:
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print(f"类别: {extraction.extraction_class}")
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print(f"文本: {extraction.extraction_text}")
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print(f"属性: {extraction.attributes}")
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print("---")
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except Exception as e:
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logger.exception("调用 langextract.extract 失败，详情：")
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raise
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@ -58,6 +58,7 @@ dependencies = [
|
||||
"jsonschema-specifications==2024.10.1",
|
||||
"kiwisolver==1.4.8",
|
||||
"langdetect==1.0.9",
|
||||
"langextract[openai]>=1.0.9",
|
||||
"markdown-it-py==3.0.0",
|
||||
"MarkupSafe==3.0.2",
|
||||
"marshmallow==3.22.0",
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142
uv.lock
generated
142
uv.lock
generated
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[package.optional-dependencies]
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{ name = "langdetect" },
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[[package]]
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name = "werkzeug"
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version = "3.1.3"
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Loading…
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Reference in New Issue
Block a user