Comments (3)
不好用呀
from baichuan2.
root@58c8455c9d58:/home/model_hub# CUDA_VISIBLE_DEVICES=1,2 python3.9 -m fastchat.serve.cli --model-path Baichuan2-13B-Chat-V1 --num-gpus 2
Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers
pip install xformers.
You are using an old version of the checkpointing format that is deprecated (We will also silently ignore gradient_checkpointing_kwargs
in case you passed it).Please update to the new format on your modeling file. To use the new format, you need to completely remove the definition of the method _set_gradient_checkpointing
in your model.
Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]/usr/local/lib/python3.9/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
return self.fget.get(instance, owner)()
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████| 3/3 [00:12<00:00, 4.14s/it]
<reserved_106>: hallo
<reserved_107>: Traceback (most recent call last):
File "/usr/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 304, in
main(args)
File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 227, in main
chat_loop(
File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/inference.py", line 532, in chat_loop
outputs = chatio.stream_output(output_stream)
File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 63, in stream_output
for outputs in output_stream:
File "/usr/local/lib/python3.9/dist-packages/torch/utils/_contextlib.py", line 56, in generator_context
response = gen.send(request)
File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/inference.py", line 190, in generate_stream
indices = torch.multinomial(probs, num_samples=2)
RuntimeError: probability tensor contains either inf
, nan
or element < 0
为啥会报这个错呀
from baichuan2.
root@58c8455c9d58:/home/model_hub# CUDA_VISIBLE_DEVICES=1,2 python3.9 -m fastchat.serve.cli --model-path Baichuan2-13B-Chat-V1 --num-gpus 2 Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers pip install xformers. You are using an old version of the checkpointing format that is deprecated (We will also silently ignore
gradient_checkpointing_kwargs
in case you passed it).Please update to the new format on your modeling file. To use the new format, you need to completely remove the definition of the method_set_gradient_checkpointing
in your model. Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]/usr/local/lib/python3.9/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() return self.fget.get(instance, owner)() Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████| 3/3 [00:12<00:00, 4.14s/it] <reserved_106>: hallo <reserved_107>: Traceback (most recent call last): File "/usr/lib/python3.9/runpy.py", line 197, in _run_module_as_main return _run_code(code, main_globals, None, File "/usr/lib/python3.9/runpy.py", line 87, in _run_code exec(code, run_globals) File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 304, in main(args) File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 227, in main chat_loop( File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/inference.py", line 532, in chat_loop outputs = chatio.stream_output(output_stream) File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/cli.py", line 63, in stream_output for outputs in output_stream: File "/usr/local/lib/python3.9/dist-packages/torch/utils/_contextlib.py", line 56, in generator_context response = gen.send(request) File "/usr/local/lib/python3.9/dist-packages/fastchat/serve/inference.py", line 190, in generate_stream indices = torch.multinomial(probs, num_samples=2) RuntimeError: probability tensor contains eitherinf
,nan
or element < 0为啥会报这个错呀
这个是baichuan2-v1.0版本
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Related Issues (20)
- LLM相同输入,多次输出不一样
- 使用fastgpt需要流式接口,请求支持 HOT 1
- 使用fastgpt框架对接baichuan2需要流式接口,请求支持 HOT 4
- 一块V100的卡,跑13b openai的启动脚本。短文本没事,文本一长就报CUDA error: out of memory。
- Baichuan2-13B-Chat-4bits 跑不起来 HOT 2
- baichuan2-13B-chat 微调loss 一直为0 HOT 2
- baichuan2-7B-chat 微调使用TrainerCallback,报错 HOT 1
- baichuan2-13b 微调后模型使用vllm输出与官方web_demo结果不一致
- 请问模型 Baichuan2-13B-Chat-4bits 支持MAC吗?
- 数据集
- 我使用了lora微调训练的4个epoch,但是模型还没有收敛,如何从保存的checkpoint继续训练
- 输入窗口是多少呢 HOT 1
- 训练和推理时数据格式不同
- 请问baichuan2的训练数据分类体系是出自哪里?
- 运行web_demo显示“'utf-8' codec can't decode bytes in position 1132-1134: invalid continuation byte”
- 可以支持ollama, 或anythingLLM 么
- ewq
- ewq
- eewr
- RuntimeError: Creating a Parameter from an instance of type Params4bit requires that detach() returns an instance of the same type, but return type Tensor was found instead. To use the type as a Parameter, please correct the detach() semantics defined by its __torch_dispatch__() implementation.
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