FanWan

Segmentation fault found when using gdb debug

1

Program received signal SIGSEGV, Segmentation fault. [Switching to Thread 0x7fffdadb1700 (LWP 14062)] 0x0000000000834cc4 in aho_corasick::state::next_state(char, bool) const () at /home/opt/compiler/gcc-8.2/gcc-8.2/include/c++/8.2.0/bits/stl_tree.h:2549 2549 _Rb_tree:: #0 0x0000000000834cc4 in aho_corasick::state::next_state(char, bool) const () at...

lower performance compared to exhaustive search ？

5

Hello, I got a performance problem about the ac machine of this project, and the following was my job. First i constructed a trie tree with 2700+ patterns and did...

我看到训练样本里面是有position特征，请问这个position特征代表的什么意思 ？？

### Is there an existing issue for this? - [X] I have searched the existing issues ### Current Behavior LR=3e-2 PRE_SEQ_LEN=128 SAVE_MODEL_PATH=chatglm_sft_0625 MASTER_PORT=$(shuf -n 1 -i 10000-65535) export CUDA_VISIBLE_DEVICES=0,1,2 deepspeed...

[BUG/Help] 使用官方代码ptuing时，推理时大量重复输出。

18

### Is there an existing issue for this? - [X] I have searched the existing issues ### Current Behavior {"labels": "樊乐,编辑,最近,,,文档", "predict": "查询一下的答案,我搜的答案,查询一下一下音量,我搜的答案,我找到答案,我再找答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答 案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,找到答案,答案,找到答案,找到答案,找到答案,找到答案,找到答案,答案,找到答案,找到答案,答案,答案,答案,找到答案,找到答案,找到答案,答案,找到答案,答案,找到答案,找到答案,答案,找到答案,找到答案,答案,找到答案,答案,答案,找到答案,答案,答案,答案,找到答案,答案,答案,找到答案,答案,答案,找到答案,找到答案,答案,答案,答案,答案,找到答案,答案,找到答案,答案,找到答案,答案,找到答案,答案,找到答案,答案,答案,找到答案,找到答案,找到答案,答案,答案,答案,找到答案,找到答案,找到答案,答案,找到答案,答案,答案,答案,找到答案,找到答案,答案,答案,答案,找到答案,答案,答案,答案,答案,找到答案,答案,答案,答案,答案,答案,找到答案,答案,答案,找到答案,答案,答案,答案,答案,找到答案,答案,答案,答案,答案,答案,答案,找到答案,答案,找到答案,找到答案,答案,答案,答案,答案,答案,找到答案,答案,答案,找到答案,找到答案,找到答案, 答案,答案,答案,找到答案,答案,答案,答案,找到答案,答案,答案,找到答案,找到答案,答案,答案,找到答案,答案,找到答案,答案,答案,找到答案,答案,答案,找到答案,答案,答案,答案,找到答案,找到答 案,答案,答案,答案,找到答案,找到答案,答案,找到答案,答案,答案,找到答案,找到答案,找到答案,答案,找到答案,答案,答案,找到答案,答案,答案,答案,答案,答案,答案,找到答案,答案,答案,答案,找到答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答 案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,找到答案,答案,答案,答案,答案,找到答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案,答案"} ### Expected Behavior...

hello，我下载了kagentlms_baichuan2_13b_mat模型，但是没办法通过fastchat部署，，以下是报错： 2024-03-11 22:02:00 | INFO | model_worker | args: Namespace(host='192.168.80.2', port=9015, worker_address='http://192.168.80.2:9015', controller_address='http://192.168.80.2:9083', model_path='/home/ssd1/record/llm_models/kagentlms_baichuan2_13b_mat/', revision='main', device='cuda', gpus=None, num_gpus=1, max_gpu_memory=None, dtype=None, load_8bit=False, cpu_offloading=False, gptq_ckpt=None, gptq_wbits=16, gptq_groupsize=-1, gptq_act_order=False, awq_ckpt=None, awq_wbits=16, awq_groupsize=-1, model_names=['kwai_agent_baichuan'],...

how to use extra settings , like OCR_ALL_PAGES ?

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marker_single --help usage: marker_single [-h] [--max_pages MAX_PAGES] [--start_page START_PAGE] [--langs LANGS] [--batch_multiplier BATCH_MULTIPLIER] [--debug] filename output when i try to use mark_single command with OCR_ALL_PAGES , i found this error....

用改框架微调GLM-4V-9B模型，存在重复输出和任务无法拟合的问题。

3

问题：训练效果不及预期 环境： 2 * A800 torch 2.2.2 torchvision 0.17.2 cuda 11.8 transformers 4.42.4 训练脚本： DATE=0719 DATA_DIR=/home/ssd1/luojinchang/swift/data/dataset_${DATE} OUTPUT_DIR=/home/ssd1/luojinchang/swift/output/glm-4v-9b-sft_${DATE} NUM_TRAIN_EPOCHS=3 LEARNING_RATE=1e-5 export CUDA_VISIBLE_DEVICES=2,3 nohup swift sft \ --model_id_or_path /home/ssd1/luojinchang/glm-4v-9b \ --model_type glm4v-9b-chat...

DocOwl1.5-Omni 推理失败

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采用官方库安装环境，推理报错。 Some weights of MPLUGDocOwlLlamaForCausalLM were not initialized from the model checkpoint at /record/llm_models/DocOwl1.5-Omni and are newly initialized: ['model.layers.9.self_attn.rotary_emb.inv_freq', 'model.layers.12.self_attn.rotary_emb.inv_freq', 'model.layers.16.self_attn.rotary_emb.inv_freq', 'model.layers.14.self_attn.rotary_emb.inv_freq', 'model.layers.24.self_attn.rotary_emb.inv_freq', 'model.layers.21.self_attn.rotary_emb.inv_freq', 'model.layers.11.self_attn.rotary_emb.inv_freq', 'model.layers.10.self_attn.rotary_emb.inv_freq', 'model.layers.4.self_attn.rotary_emb.inv_freq', 'model.layers.7.self_attn.rotary_emb.inv_freq', 'model.layers.5.self_attn.rotary_emb.inv_freq', 'model.layers.23.self_attn.rotary_emb.inv_freq',...