函数preprocess_function的实现(示例)可在附带的Colab Notebook中获得(参见下面的链接)。 我们使用Huggingface Datasets mapmethod对整个数据集应用预处理函数。我们可以通过设置batched=True来一次处理数据集的多个元素来加速map函数: tokenized_billsum = billsum.map(preprocess_function, batched=True) 预处理后,tokeniz...
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Finally, we convert the pre-trained model into Huggingface's format: python3 scripts/convert_t5_from_uer_to_huggingface.py --input_model_path models/cluecorpussmall_t5_small_seq512_model.bin-250000 \ --output_model_path pytorch_model.bin \ --layers_num 6 \ --type t5 ...
PyTorch version (GPU?): No GPU , >- 1.3 Using GPU in script?: No Using distributed or parallel set-up in script?: No Who can help Models: t5:@patrickvonplaten,@patil-suraj Library: tokenizers:@LysandreJik Looks like this is an issue with the t5Tokenizer possibly? - Seems related to...
bash inductor_single_run.sh multiple inference performance huggingface T5Small amp first dynamic cpp Suspected guilty commit:b7d287f huggingface-T5Small-inference-amp-dynamic-cpp-multiple-performance-drop_guilty_commit.log cc@ezyang@anijain2305@chauhang@penguinwu@WeizhuoZhang-intel@chuanqi129 ...