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import dill
from transformers import PreTrainedModel, PretrainedConfig
class CountAModel(PreTrainedModel):
config_class = PretrainedConfig
def __init__(self, config):
super().__init__(config)
def forward(self, text):
return text.lower().count('a')
def save_pretrained(self, save_directory):
self.config.save_pretrained(save_directory)
config = PretrainedConfig()
config.torch_dtype = 'float32' # Add a dummy torch_dtype attribute
config.model_type = 'CountA'
model = CountAModel(config)
# Validate
sentence = "This is a sample sentence with a few 'a's."
count_a = model(sentence)
print(f"The sentence contains {count_a} letter(s) 'a'.")
# Save the model in the current directory
model.save_pretrained(".")
with open('example-dummy-evaluation.dill', 'wb') as f:
dill.dump(model, f)
dill.dump(CountAModel, f)
print("Model saved successfully.")
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