对于Logits processor,huggingface的generate()函数在进行next token生成的时候,每次生成一个新的token都会调用在generate()函数调用时传入的logits processor对niput_ids以及scores进行处理: def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor: num_batch_hypotheses =...
Hugging Face 是自然语言处理 (NLP) 模型的开源提供商。Amaz SageMaker on Python 软件开发工具包HuggingFaceProcessor中的让你能够使用 Hugging Face 脚本运行处理作业。在使用HuggingFaceProcessor时,您可以利用 Amazon 构建的 Docker 容器和托管的 Hugging Face 环境,这样您便无需自带容器。
I added support for SAM to work with model data that was on HuggingFace in #49, so we can wait for that PR or grab the changes there into a separate one. 👍 1 patrickvonplaten reviewed Jun 1, 2023 View reviewed changes src/controlnet_aux/processor.py """ print(f"Loading {...
uniformize processor Mllama #33876 Merged yonigozlan merged 3 commits into huggingface:main from yonigozlan:uniformize-processor-mllama Oct 2, 2024 Merged uniformize processor Mllama #33876 yonigozlan merged 3 commits into huggingface:main from yonigozlan:uniformize-processor-mllama Oct 2, ...
The HuggingFaceProcessor in the Amazon SageMaker Python SDK provides you with the ability to run processing jobs with Hugging Face scripts. When you use the HuggingFaceProcessor, you can leverage an Amazon-built Docker container with a managed Hugging Face environment so that you don't need to ...
class ProcessorGradientFlow(): """ This wraps the huggingface CLIP processor to allow backprop through the image processing step. The original processor forces conversion to numpy then PIL images, which is faster for image processing but breaks gradient flow. """ def __init__(self, device="cu...
absoluta o de Amazon S3. Sin embargo, si utiliza un URI de Amazon S3, debe apuntar a un archivo tar.gz. Puede tener varios scripts en el directorio que especifique parasource_dir. Para obtener más información sobre laHuggingFaceProcessorclase, consulteHugging FaceEstimator en el SDK de ...
Easy and lightning fast training of 🤗 Transformers on Habana Gaudi processor (HPU) - huggingface/optimum-habana
from sagemaker.huggingface import HuggingFaceProcessor from sagemaker.processing import ProcessingInput, ProcessingOutput from sagemaker import get_execution_role #Initialize the HuggingFaceProcessor hfp = HuggingFaceProcessor( role=get_execution_role(), instance_count=1, instance_type='ml.g4dn.xlarge', tra...
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. - Fast image processor (#28847) · huggingface/transformers@f53fe35