Comments (2)
yes, it is bit confusing, it should be model_name
, not model_name_or_path
, I'll make this change in the next update.
the purpose of the model_name
(the current model_name_or_path
) is to select a particular model from a custom folder if you've stored more than one type of model in that folder.
the export_and_get_onnx_model() method could save the model name configuration in the ONNX folder and could arrange a standard model name for ONNX files names as we can now (in the latest version of fastt5) customize ONNX folder path.
can you elaborate more on this.
from fastt5.
it should be
model_name
, notmodel_name_or_path
I agree. This is exactly my point: the name of the model is important to get back our ONNX model with get_onnx_model()
, not the path to the model.
My second point is that get_onnx_model()
calls the class OnnxT5 in step 4, and this class is initialized with the following code:
config = AutoConfig.from_pretrained(
model_or_model_path, use_auth_token=get_auth_token()
)
I think we could save the config
file through export_and_get_onnx_model()
. If not, we need model_or_model_path
as argument of get_onnx_model()
but we do not want that.
from fastt5.
Related Issues (20)
- Support for py3.10 HOT 1
- Fails to convert T0-3B HOT 2
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