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
Hi there, I'm wondering if there is an example of how to use this repo to pretrain T5?
I saw this file and thought that it could maybe serve as a start to an example. But when I try to run it, I get this error:
(benchmarking) tristan_huggingface_co@tristan-olm-training-a100-80:~/oslo/tests/transformers/models/mt5$ python test_training.py Downloading builder script: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 28.8k/28.8k [00:00<00:00, 351kB/s] Downloading metadata: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 28.7k/28.7k [00:00<00:00, 9.87MB/s] Downloading and preparing dataset glue/sst2 (download: 7.09 MiB, generated: 4.81 MiB, post-processed: Unknown size, total: 11.90 MiB) to /home/tristan_huggingface_co/.cache/huggingface/datasets/glue/sst2/1.0.0/dacbe3125aa31d7f70367a07a8a9e72a5a0bfeb5fc42e75c9db75b96da6053ad... Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7.44M/7.44M [00:01<00:00, 5.51MB/s] Dataset glue downloaded and prepared to /home/tristan_huggingface_co/.cache/huggingface/datasets/glue/sst2/1.0.0/dacbe3125aa31d7f70367a07a8a9e72a5a0bfeb5fc42e75c9db75b96da6053ad. Subsequent calls will reuse this data. 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 698.12it/s] 0%| | 0/68 [00:00<?, ?ba/s] Traceback (most recent call last): File "test_training.py", line 60, in <module> processed_dataset = dataset.map( File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/dataset_dict.py", line 771, in map { File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/dataset_dict.py", line 772, in <dictcomp> k: dataset.map( File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2449, in map return self._map_single( File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 577, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 544, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/fingerprint.py", line 480, in wrapper out = func(self, *args, **kwargs) File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2849, in _map_single batch = apply_function_on_filtered_inputs( File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2729, in apply_function_on_filtered_inputs processed_inputs = function(*fn_args, *additional_args, **fn_kwargs) File "/home/tristan_huggingface_co/anaconda3/envs/benchmarking/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2409, in decorated result = f(decorated_item, *args, **kwargs) File "/home/tristan_huggingface_co/oslo/oslo/transformers/tasks/data_t5_pretraining.py", line 57, in __call__ list_of_input_ids: List[List[int]] = self._tokenizer( TypeError: 'str' object is not callable
Separately, I had to downgrade my version of datasets to get this far.
datasets
Thanks for any help that anyone can give! TLDR: I'm wondering if there is a working example of T5 pretraining
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Hi there, I'm wondering if there is an example of how to use this repo to pretrain T5?
I saw this file and thought that it could maybe serve as a start to an example. But when I try to run it, I get this error:
Separately, I had to downgrade my version of
datasets
to get this far.Thanks for any help that anyone can give! TLDR: I'm wondering if there is a working example of T5 pretraining
The text was updated successfully, but these errors were encountered: