执行第三步后,正常生成的文件是这几个吗? 最后执行python3 run.py --tokenizer_dir=Qwen-14B-Chat-Int4,发现预测结果不对,本次预测结果为: ,请问如何解决这个问题?takemars changed the title Qwen-7B-Chat-Int4运行后预测结果不对 Qwen-14B-Chat-Int4运行后预测结果不对 Jan 25, 2024 Author takemars ...
load_model_and_preprocess=partial(load_model_and_preprocess,is_eval=True,device="cuda")llm_device_map="auto"model,vis_processors,_=load_model_and_preprocess("minigpt4qwen","qwen14b_chat",llm_device_map=llm_device_map) 参考repo中给定的jupyter notebook:https://github.com/Coobiw/MiniGPT4Qwe...
When i use python_api_example or streaming_llm python scripts to inference Qwen-14B-Chat,the first two questions were outputted normally, but the third question has been repeating itself since then. I find it strange and can stably reproduce this error. And it seems like something has been ...
git clone https://github.com/QwenLM/Qwen.git 然后安装modelscope基础库 pip install modelscope 然后安装量化依赖 pip install auto-gptq optimum 然后安装量化包 pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui 安装其他依赖,这里不解释...
"Qwen-14B-Chat", "Qwen-7B-Chat", ] LLM_MODEL_CONFIG = { # 意图识别不需要输出,模型后台知道就行 "preprocess_model": { "zhipu-api": { "temperature": 0.4, "max_tokens": 2048, "history_len": 100, "chatglm3-6b": { "temperature": 0.01, ...
已加入MiniGPT4Qwen-14B-Chat模型的双卡DeepSpeed流水线并行训练,后续的推理(命令行demo+ gradio WebUI demo),以及14B模型的checkpoint和train log(流水线并行14B模型的权重和日志)。如果有帮助,可以考虑star一下,马上300个了!有相关问题和建议也可以github上直接提issue,会比知乎戳我更快!
Closed Contributor jklj077 commented Jan 2, 2024 是的预期内行为,vLLM需要单独传入stop_token_ids来中止。建议参考README使用FastChat+vLLM。 jklj077 closed this as completed Jan 2, 2024 Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees...
可以看到,Qwen-14B-Chat的Tokenizer的压缩能力更强,尤其sft阶段,选择max_length为512就可以很好的完成sft,我们的6卡RTX 4090完全可以满足。根据分析结果,MPP-Qwen-14B在预训练阶段的max_length为256,sft阶段的max_length为512。 训练流程和曲线分析 训练流程 ...
使用Qwen1.5-14b-chat或者Qwen1.5-32b-chat-awq,用英文提问时均会有概率出现中英混杂的情况 #302 Closed lin-xiaosheng opened this issue Apr 13, 2024· 8 comments Closed 使用Qwen1.5-14b-chat或者Qwen1.5-32b-chat-awq,用英文提问时均会有概率出现中英混杂的情况 #302 lin-xiaosheng opened this ...
9月25日,阿里云开源通义千问140亿参数模型Qwen-14B及其对话模型Qwen-14B-Chat,免费可商用。Qwen-14B在多个权威评测中超越同等规模模型,部分指标甚至接近Llama2-70B。阿里云此前开源的70亿参数模型Qwen-7B等,一个多月下载量破100万,成为开源社区的口碑之作。 Qwen-14B是一款支持多种语言的高性能开源模型,相比同类模...