Huggingface 3B and 11B models not configured properly

Hello, it seems that the models are not properly configured on huggingface so it is not possible to download and use them using the given snippets in the readme. If you try to do so using the code snippet in the readme:

from transformers import AutoTokenizer, T5ForConditionalGeneration

model_name = "allenai/unifiedqa-t5-3b" # you can specify the model size here
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

The following error occurs:

OSError                                   Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    927                 if resolved_archive_file is None:
--> 928                     raise EnvironmentError
    929             except EnvironmentError:

OSError: 

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
1 frames
/usr/local/lib/python3.6/dist-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    933                     f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a file named one of {WEIGHTS_NAME}, {TF2_WEIGHTS_NAME}, {TF_WEIGHTS_NAME}.\n\n"
    934                 )
--> 935                 raise EnvironmentError(msg)
    936 
    937             if resolved_archive_file == archive_file:

OSError: Can't load weights for 'allenai/unifiedqa-t5-3b'. Make sure that:

- 'allenai/unifiedqa-t5-3b' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'allenai/unifiedqa-t5-3b' is the correct path to a directory containing a file named one of pytorch_model.bin, tf_model.h5, model.ckpt.

On huggingface, both the 3B model and the 11B do not seem to have the weights file when you list the model files, which is probably the cause of the issue. Is this a mistake or is it on purpose? Because the original T5-11B model has all the weight files on huggingface as expected.

PS: The large model example in the readme also seems to be mistyped, using allenai/unifiedqa-t5-large instead of allenai/unifiedqa-large

Thanks!

[PeterAJansen]

Aha – I’m finally able to replicate (and solve) it.

Case 1 (Works): Using the official transformers 4.2.1 release: peter@neutronium:~/github/transformers-t5-a100$ pip install transformers==4.2.1

Case 2 (doesn’t work): Using a very recent but not this-minute transformers clone (I think from the last 1-2 days): peter@neutronium:~/github/transformers-t5-a100$ pip install .

Case 3 (works): Using a completely fresh clone made minutes ago (where things in seq2seq seem to have significantly changed): peter@neutronium:~/github/transformers/examples/seq2seq$ python finetune_trainer.py --data_dir $XSUM_DIR --output_dir=xsum_results --num_train_epochs 1 --model_name_or_path allenai/unifiedqa-t5-11b (this one produces a lot of output, but also starts downloading the model successfully).

In summary: I have no idea what’s wonky about the pull I’ve been using from the last few days, but there seem to have been significant changes today, and it now fetches 11B successfully too.

Only in transformers can the library you’re using change significantly over hours… thanks for your help!

[danyaljj]

The issue should be resolved now, as per this conversation: https://github.com/huggingface/transformers/issues/8480 Let me know if you see any issue @Shamdan17.