Yes, the two links above. It's both on the same dataset. One is a BoW model, one is a BERT model.
@rasbt
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Adapter v2 and Video-LLaMA Models Available
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There's both, adapter v2 and e.g., Video-LLaMA https://
github.com/DAMO-NLP-SG/Vi
deo-LLaMA
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Comparison of BOW and BERT Performance on Text Classification Tasks
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The results for the 150 texts are from a paper (unpublished); from a collaboration so I can't share, yet. But I do also have examples on GitHub with a different dataset (from my course) here: 88% acc BOW: https://
github.com/Lightning-AI/d
l-fundamentals/blob/main/unit08-large-language-models/8.2-bag-of-words/8.2-part2-bag-of-words-classifier.ipynb
… 92.6% acc BERT: https://
github.com/Lightning-AI/d
l-fundamentals/blob/main/unit08-large-language-models/8.7-distilbert-finetuning/part3_distilbert-finetuning-whole.ipynb
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Open Source Models Now Support Multiple Media Types Beyond Images
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Yeah, in the demo they showed a version that supported images. But still, afaik it was only images whereas there are now open source models that also support audio, video, etc.
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Open-source multimodal models ahead of GPT-4
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Second, there are already several multimodal models out there; GPT-4 is still a pure text model. Here’s where open-source innovated first.
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Open-Source Model Finetuning Outperforms Generalist Models
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Disagree. You can finetune open-source models. And if done right, finetuned models outperform generalist models. You can’t finetune GPT-4 w/o access.
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Advanced Machine Learning and Deep Learning Resource Release Announcement
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I am really excited with how it turned out. Finally a resource for those who are interested in a bit more advanced machine learning, deep learning, and AI topics. PS: I also partnered with a publisher to also release print version later this summer. Stay tuned! 3/3
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New Book Machine Learning Q and AI Released Today
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Today is the day! My new book Machine Learning Q and AI is now complete! https://
leanpub.com/machine-learni
ng-q-and-ai/
… Covering – Explanations of multi-GPU training paradigms.
– Using and finetuning transformers.
– Differences between encoder- and decoder-style LLMs.
– And many more! 1/3 -
ViT and MobileViT Computational Performance Benchmark for CVPR
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just the original ViT and MobileViT via timm. It was for a computational performance benchmark (preparing sth for CVPR)
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Fine-tuning Vision Transformers shows promising results
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I'd say so! Recently finetuned a couple of ViTs and it worked pretty well actually.