- 模型推理测试
- 微调前的chatglm2-6b模型
- 运行
python predict.py --mode glm2 --model_path chatglm2-6b/
- 运行结果记录
bash
复制代码
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
2024-11-08 17:21:16.440515: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-08 17:21:16.562434: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-11-08 17:21:17.121689: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:21:17.121775: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:21:17.121784: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s]/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/modeling_utils.py:488: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
return torch.load(checkpoint_file, map_location=map_location)
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████| 7/7 [00:10<00:00, 1.52s/it]
根据您提供的文本，我可以抽取出以下三个相关三元组：
1. 性能故障 -> 发动机水温高
2. 部件故障 -> 风扇始终是低速转动
3. 组成 -> 高速档不工作
4. 检测工具 -> 开空调
其中，第一个三元组表示发动机出现了性能故障，导致发动机水温高。第二个三元组表示风扇出现了部件故障，始终是低速转动。第三个三元组表示高速档不工作，可能是由于某个部件出现了问题。最后一个三元组表示开空调时出现了性能故障。
- 微调后的chatglm2-6b模型
- 运行
python predict.py --mode glm2 --model_path output-glm2/epoch-1-step-90/
- 运行结果记录
bash
复制代码
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
2024-11-08 17:30:12.764824: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-08 17:30:12.887176: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-11-08 17:30:13.455307: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:30:13.455391: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:30:13.455400: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s]/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/modeling_utils.py:488: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
return torch.load(checkpoint_file, map_location=map_location)
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████| 7/7 [00:10<00:00, 1.55s/it]
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/peft/utils/save_and_load.py:198: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
adapters_weights = torch.load(filename, map_location=torch.device(device))
发动机_部件故障_水温高
风扇_部件故障_始终是低速转动
高速档_部件故障_不工作
- 运行
python predict.py --mode glm2 --model_path output-glm2/epoch-2-step-180/
- 运行结果记录
bash
复制代码
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
2024-11-08 17:34:23.878094: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-08 17:34:24.001155: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-11-08 17:34:24.560807: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:34:24.560894: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.8/lib64:/usr/local/cuda-11.8/lib64:
2024-11-08 17:34:24.560903: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/utils/generic.py:311: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
torch.utils._pytree._register_pytree_node(
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s]/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/transformers/modeling_utils.py:488: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
return torch.load(checkpoint_file, map_location=map_location)
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████| 7/7 [00:10<00:00, 1.55s/it]
/data/user23262833/.conda/envs/chatglm/lib/python3.8/site-packages/peft/utils/save_and_load.py:198: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
adapters_weights = torch.load(filename, map_location=torch.device(device))
发动机_部件故障_水温高
风扇_部件故障_低速转动
高速档_部件故障_不工作