runtime error

Exit code: 1. Reason: 2024-12-04 14:02:47.901046: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. All model checkpoint layers were used when initializing TFT5ForConditionalGeneration. All the layers of TFT5ForConditionalGeneration were initialized from the model checkpoint at t5-base. If your task is similar to the task the model of the checkpoint was trained on, you can already use TFT5ForConditionalGeneration for predictions without further training. Downloading spiece.model: 0%| | 0.00/773k [00:00<?, ?B/s] Downloading spiece.model: 100%|██████████| 773k/773k [00:00<00:00, 51.6MB/s] Downloading tokenizer.json: 0%| | 0.00/1.32M [00:00<?, ?B/s] Downloading tokenizer.json: 100%|██████████| 1.32M/1.32M [00:00<00:00, 48.8MB/s] /usr/local/lib/python3.10/site-packages/transformers/models/t5/tokenization_t5_fast.py:156: FutureWarning: This tokenizer was incorrectly instantiated with a model max length of 512 which will be corrected in Transformers v5. For now, this behavior is kept to avoid breaking backwards compatibility when padding/encoding with `truncation is True`. - Be aware that you SHOULD NOT rely on t5-base automatically truncating your input to 512 when padding/encoding. - If you want to encode/pad to sequences longer than 512 you can either instantiate this tokenizer with `model_max_length` or pass `max_length` when encoding/padding. - To avoid this warning, please instantiate this tokenizer with `model_max_length` set to your preferred value. warnings.warn( Traceback (most recent call last): File "/home/user/app/app.py", line 13, in <module> inputs=gr.inputs.Textbox(lines=10, placeholder="Enter Text Here..."), AttributeError: module 'gradio' has no attribute 'inputs'

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