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Machine Learning

[Solved] Some weights of the model checkpoint at distilbert-base-multilingual-cased were not used when initializing DistilBertForSequenceClassification: [‘vocab_projector.bias’, ‘vocab_layer_norm.bias’, ‘vocab_layer_norm.weight’, ‘vocab_transform.weight’, ‘vocab_transform.bias’]

Problem

When using the transformers package, often we receive the following error message when we utilize different task models with various heads like AutoModelForSequenceClassification, AutoModelForSeq2SeqLM…

Read More »[Solved] Some weights of the model checkpoint at distilbert-base-multilingual-cased were not used when initializing DistilBertForSequenceClassification: [‘vocab_projector.bias’, ‘vocab_layer_norm.bias’, ‘vocab_layer_norm.weight’, ‘vocab_transform.weight’, ‘vocab_transform.bias’]

[Solved] UserWarning: CUDA initialization: CUDA unknown error – this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at …/c10/cuda/CUDAFunctions.cpp:109.) return torch._C._cuda_getDeviceCount() > 0

Problem

Today when I training the model on my server, I write an GPU parallel training script, and input the newest training data; but in the process of training, I got an error message about “GPU not found“. After I using torch.cuda.is_available() to check my device, I got another error message as following:

Read More »[Solved] UserWarning: CUDA initialization: CUDA unknown error – this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at …/c10/cuda/CUDAFunctions.cpp:109.) return torch._C._cuda_getDeviceCount() > 0

ImageBind: A Experience Notes on a Multimodal Vector Transformation Model

Introduction

Meta AI has indeed been incredibly powerful recently, seemingly securing its position as a giant in AI research and development in no time at all, and what’s more, it sets the bar high with all its top-tier open-source contributions. From Segment Anything that can segment objects in the image domain, to the public large language model and foundational model, LLaMA (yes, the one causing the llama family appear!), to the recent ImageBind that can transform six modalities and the Massively Multilingual Speech (MMS) project… I must say, for an ordinary person like me, it’s quite an effort to keep up with how to use these technologies, let alone trying to chase their technical prowess.

Read More »ImageBind: A Experience Notes on a Multimodal Vector Transformation Model

[Solved] HuggingFace Transformers Model Return “‘ValueError: too many values to unpack (expected 2)’, upon training a Bert binary classification model”

In the current deep learning framework, whether using Tensorflow, PyTorch or others… the input and output of the model, the flow of data, we need to pay great attention to the shape of data. Because if you are not careful, the model will return an error message.

Read More »[Solved] HuggingFace Transformers Model Return “‘ValueError: too many values to unpack (expected 2)’, upon training a Bert binary classification model”