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进行模型预测时报错,以下是预测参数: CUDA_VISIBLE_DEVICES=0,2 python dbgpt_hub/predict/predict.py --model_name_or_path /data/nfsshare/llama-3-sqlcoder-8b-bak/app/model --template llama2 --finetuning_type lora --predicted_input_filename dbgpt_hub/data/pred/text2sql_列表类.json --checkpoint_dir dbgpt_hub/output/adapter/llama3-sqlcoder-lora --predicted_out_filename dbgpt_hub/output/pred/pred_列表类.sql >> ${pred_log}
训练的时候也是采用lora的训练方式
The text was updated successfully, but these errors were encountered:
这个应该是因为,训练的结果是用safetensor保存的,但是预测模型的时候,却使用了bin格式进行加载,导致文件不匹配。
训练方式,codellama模型,不使用deepspeed,使用sft训练
ref:huggingface/safetensors#397 (comment)
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用下面的代码转换一下(亲测有效): from safetensors.torch import load_file import torch lora_model_path = 'adapter_model.safetensors' bin_model_path = 'adapter_model.bin'
torch.save(load_file(lora_model_path), bin_model_path)
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进行模型预测时报错,以下是预测参数:
CUDA_VISIBLE_DEVICES=0,2 python dbgpt_hub/predict/predict.py
--model_name_or_path /data/nfsshare/llama-3-sqlcoder-8b-bak/app/model
--template llama2
--finetuning_type lora
--predicted_input_filename dbgpt_hub/data/pred/text2sql_列表类.json
--checkpoint_dir dbgpt_hub/output/adapter/llama3-sqlcoder-lora
--predicted_out_filename dbgpt_hub/output/pred/pred_列表类.sql >> ${pred_log}
训练的时候也是采用lora的训练方式
The text was updated successfully, but these errors were encountered: