Hi. I have fine-tuned a model, then save it to local disk. But when I load my local mode with pipeline, it looks like pipeline is finding model from online repositories. How can i fix it ? Please help.
My code for training and save model to local disk:
from transformers import Seq2SeqTrainingArguments
training_args = Seq2SeqTrainingArguments(
Then I load it to pipeline:
from transformers import pipeline
pipe = pipeline(model="./my_local_disk")
But I got this error when create pipeline object:
OSError: ./my_local_disk does not appear to have a file named config.json.
Checkout 'https://huggingface.co/./my_local_disk/None' for available files.
It looks like pipeline is loading from online repositories, not my local folder. Please help me fix it
you can use absolute path
sorry but still same error.
I am running notebooks code in colab, so my absoluted path is
But even when I use absoluted path, it still show error:
OSError: /content/my_local_disk does not appear to have a file named config.json. Checkout 'https://huggingface.co//content/my_local_disk/None' for available files.
Sorry but can anyone help ??
please can anyone help me ?
i am stucked at this step
The “output_dir” on training args is for saving the checkpoints during refinement. You need to call
save_model on your
Trainer instance to actually save the model.
thank you for your help. And after that, how can I load saved model ?
Do I still need to define
Trainer again ? In this case, I think using pipeline will be better, because we don’t need to duplicated code to define
Once you save the model, you can provide the path to the saved model just as you would provide the path to any model. Your code sample was the correct way to load it.