Zero-shot Learning by Generating Task-specific Adapters

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Deep Learning hypter
Overview

Code for "Zero-shot Learning by Generating Task-specific Adapters"

This is the repository containing code for "Zero-shot Learning by Generating Task-specific Adapters" (arXiv). This is a beta version and we will add more details in the future.

Environment

We modified the code in shmsw25/bart-closed-book-qa (Thanks to the authors!).

Following their instructions, please install the environment with these commands:

pip install torch==1.1.0
pip install git+https://github.com/huggingface/transformers.git@7b75aa9fa55bee577e2c7403301ed31103125a35

Data

Download ZEST dataset from here and place (zest_{train|dev|test_unanswered}.jsonl) in ./data.

Run

See ./scripts/zest_bart_large.sh and ./scripts/zest_grouped_bart_large_from_trained.sh

Cite Us

@article{Ye2021ZeroshotLB,
  title={Zero-shot Learning by Generating Task-specific Adapters},
  author={Qinyuan Ye and Xiang Ren},
  journal={ArXiv},
  year={2021},
  volume={abs/2101.00420}
}
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Comments
  • model too large for forwarding by gpu in collab?

    model too large for forwarding by gpu in collab?

    i met this error when run ./scripts/zest_grouped_bart_large_from_trained.sh Epoch 0: 0% 0/538 [00:00<?, ?it/s] Traceback (most recent call last): File "cli_grouped.py", line 142, in main() File "cli_grouped.py", line 139, in main run(args, logger) File "/content/drive/MyDrive/hypter/run_grouped.py", line 87, in run train(args, logger, model, train_data, dev_data, optimizer, scheduler) File "/content/drive/MyDrive/hypter/run_grouped.py", line 154, in train is_training=True) File "/content/drive/MyDrive/hypter/growing_bart.py", line 119, in forward is_training=is_training File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/content/drive/MyDrive/hypter/bart_with_adapter.py", line 298, in forward use_cache=use_cache, File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/usr/local/lib/python3.7/dist-packages/transformers/modeling_bart.py", line 835, in forward encoder_outputs = self.encoder(input_ids=input_ids, attention_mask=attention_mask) File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/usr/local/lib/python3.7/dist-packages/transformers/modeling_bart.py", line 309, in forward x, attn = encoder_layer(x, attention_mask) File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/content/drive/MyDrive/hypter/bart_with_adapter.py", line 138, in forward query=x, key=x, key_padding_mask=encoder_padding_mask, need_weights=self.output_attentions File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/usr/local/lib/python3.7/dist-packages/transformers/modeling_bart.py", line 646, in forward attn_weights = attn_weights.masked_fill(reshaped, float("-inf")) RuntimeError: CUDA out of memory. Tried to allocate 256.00 MiB (GPU 0; 14.76 GiB total capacity; 13.24 GiB already allocated; 81.75 MiB free; 13.29 GiB reserved in total by PyTorch) Is model too large for forwarding by gpu in collab?

    opened by trinh-hoang-hiep 1
Owner
INK Lab @ USC
Intelligence and Knowledge Discovery (INK) Research Lab at University of Southern California
INK Lab @ USC
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