LANGFUSE_INIT_USER_PASSWORD: ${LANGFUSE_INIT_USER_PASSWORD:-} LANGFUSE_SDK_CI_SYNC_PROCESSING_ENABLED: ${LANGFUSE_SDK_CI_SYNC_PROCESSING_ENABLED:-false} LANGFUSE_READ_FROM_POSTGRES_ONLY: ${LANGFUSE_READ_FROM_POSTGRES_ONLY:-false} LANGFUSE_READ_FROM_CLICKHOUSE_ONLY: ${LANGFUSE_READ_FROM_C...
Langfuse已支持OpenAI,因此调用方式非常简单,代码如下: fromdotenvimportload_dotenvfromlangfuse.decoratorsimportobservefromlangfuse.openaiimportopenaiload_dotenv()@observe()defstory():response=openai.chat.completions.create(model="gpt-4o",messages=[{"role":"user","content":"What is Langfuse?"}],)retu...
这儿,我们执行完成之后检查一下“/fds”目录下是否有我们指定的内容。更多后置命令的介绍可参考后面高级功能介绍。 训练结果 训练完成后,我们检查结果文件是否都存在,下面是我们示例程序运行的结果: Cloud-ML提供了ModelService和Tensorboard的功能,可以对这些结果进行下一步操作,请移步相关文档。 同时我们看一下Log的输...
runtime::TypedPackedFunc<Function(Function, IRModule, PassContext)> pass_func = [=](Function f, IRModule m, PassContext pc) {boollink_params =false; Executor executor = m->GetAttr<Executor>(tvm::attr::kExecutor).value_or(NullValue<Executor>()); link_params = executor.defined() ? exec...
pip install "modelscope>=1.9.1" pip install auto_gptq 推理代码: import os import torch import time from modelscope import AutoTokenizer, snapshot_download from auto_gptq import AutoGPTQForCausalLM os.environ["TOKENIZERS_PARALLELISM"] = "false" def load_model_tokenizer(model_path): """ Lo...
model = AutoGPTQForCausalLM.from_quantized(model_path, inject_fused_attention=False, inject_fused_mlp=False, use_cuda_fp16=True, disable_exllama=False, device_map='auto' # Support multi-gpus ) return model, tokenizer def inference(model, tokenizer, prompt): """ Uset the given model and...
inject_fused_attention=False, inject_fused_mlp=False, use_cuda_fp16=True, disable_exllama=False, device_map='auto' # Support multi-gpus ) return model, tokenizer def inference(model, tokenizer, prompt): """ Uset the given model and tokenizer to generate an answer for the speicifed prompt...
ModelScope 地址:https://modelscope.cn/datasets/codefuse-ai/CodeFuseEval 评测数据集构建 根据不同的任务类型,我们构建动态代码评测集对当前代码大模型不同类型任务进行持续评估。评测数据集按照来源可分为:开源评测集、内部数据评测集、众测数据、待训数据集按比例划分; ...
e>然后就是由model生成CRUD运行mvnappfuse:gen-Dentity=Employee会生成employeeList.jsp、employeeForm.jsp、EmployeeAction.java但是没有自动生成dao与service而是采用的GenericManager<Employee,Long>中的方法,解决方法如下: 在项目下的pom.xml中查找genericCore,大概在940行找到将属性true改为false ...
Note: We recommend using our fully async, typed SDKs that allow you to instrument any LLM application with any underlying model. They are available in Python (Decorators) & JS/TS. The SDKs will always be the most fully featured and stable way to ingest data into Langfuse....