We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
optimum==1.17.0.dev0
No response
examples
The given code
from optimum.onnxruntime import ORTModelForCausalLM from transformers import BitsAndBytesConfig finetuned_model_name = "path" import torch compute_dtype = getattr(torch, "float16") bnb_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=compute_dtype, bnb_4bit_use_double_quant=False) ort_model = ORTModelForCausalLM.from_pretrained( finetuned_model_name, use_io_binding=True, quantization_config=bnb_config, export=True, use_cache=True, from_transformers=True )
shows the errror
TypeError: _from_transformers() got an unexpected keyword argument 'quantization_config'
so how to do quantization while loading with ORTModelForCausalLM
The text was updated successfully, but these errors were encountered:
No branches or pull requests
System Info
Who can help?
No response
Information
Tasks
examples
folder (such as GLUE/SQuAD, ...)Reproduction (minimal, reproducible, runnable)
The given code
shows the errror
so how to do quantization while loading with ORTModelForCausalLM
Expected behavior
The given code
shows the errror
so how to do quantization while loading with ORTModelForCausalLM
The text was updated successfully, but these errors were encountered: