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I follow the example from README except for the part where model is being quantized
from fastT5 import (OnnxT5, get_onnx_runtime_sessions,
generate_onnx_representation, quantize)
from transformers import AutoTokenizer
model_or_model_path = 't5-small'
# Step 1. convert huggingfaces t5 model to onnx
onnx_model_paths = generate_onnx_representation(model_or_model_path)
model_sessions = get_onnx_runtime_sessions(onnx_model_paths)
however get_onnx_runtime_sessions is killing the kernel, what's wrong? same for
from fastT5 import export_and_get_onnx_model
from transformers import AutoTokenizer
model_name = 't5-small'
model = export_and_get_onnx_model(model_name, quantized=False)
I'm using
fastt5==0.1.4
torch==1.13.1
onnx==1.8.0
The text was updated successfully, but these errors were encountered:
I follow the example from README except for the part where model is being quantized
however get_onnx_runtime_sessions is killing the kernel, what's wrong? same for
I'm using
fastt5==0.1.4
torch==1.13.1
onnx==1.8.0
The text was updated successfully, but these errors were encountered: