RuntimeError: Failed to import transformers.trainer because of the following error (look up to see its traceback): cannot import name 'check_peft_version' from 'transformers.utils' (/miniconda3/lib/python3.10/site-packages/transformers/utils/__init__.py) I'm sorrytransformers-cli envdoesn't ...
For these two models, whether it's LLM or VLM, the transformers_version field is located in the config.json top-level directory. However, in InternVL2, it is located in the llm_config secondary directory. I don't know if this kind of fix can cover all situations currently. Do you ...
def check_pipeline_consistency(name, estimator_orig): if name in ('CCA', 'LocallyLinearEmbedding', 'KernelPCA') and _is_32bit(): # Those transformers yield non-deterministic output when executed on # a 32bit Python. The same transformers are stable on 64bit Python. # FIXME: try to iso...
GPT, or Generative Pre-trained Transformers, are a class oflarge language modelsthat excel in various NLP tasks. They are known for their ability to generate coherent and contextually relevant text by leveraging knowledge extracted from massive amounts of training data. GPT models can be integrated...
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+1 看到同样的事情。
...错误示例: from transformers import BertTokenizer 如果你看到如下错误: ImportError: cannot import name 'BertTokenizer...总结 ImportError: cannot import name 'BertTokenizer' from 'transformers' 是一个相对常见的错误,特别是在库频繁更新的情况下。
SageMaker smart sifting within your training script Apply SageMaker smart sifting to your PyTorch script Apply SageMaker smart sifting to your Hugging Face Transformers script Troubleshooting Security in SageMaker smart sifting SageMaker smart sifting Python SDK reference Release notes ...
The following code snippet shows an example structure of a training script using the AutoModelForCausalLM class of Hugging Face Transformers with modifications for registering the smdistributed.model.parallel.torch modules and settings for fine-tuning....
Results suggest it can deliver ~24x higher throughput than HuggingFace Transformers without requiring any model changes. As a result, it makes LLM serving much more affordable for everyone. Get started here:vLLM GitHub. #2) CTranslate2