Maybe this installation + requirements.txt from my recent DL workshop is useful here: https://
github.com/rasbt/scipy202
3-deeplearning/tree/main/00-2_python-libraries-for-workshop
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OPEN SOURCE
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Installation and requirements setup for deep learning workshop
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Power User PyTorch Nightly and Lightning GitHub Installation
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As a "power user" I usually install the PyTorch nightly and the lightning from the GitHub branch .
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AlphaFold Adoption Accelerates Lifesaving Medical Research Workflows
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I’ve been so impressed by how quickly scientists have adapted #AlphaFold into their daily workflows and use it to advance their important work on lifesaving treatments. This is exactly why we made it freely available to the research community. https://t.co/sxaXe3fBh6 pic.twitter.com/XyDlPfScWy
— Demis Hassabis (@demishassabis) 7 août 2023I’ve been so impressed by how quickly scientists have adapted #AlphaFold into their daily workflows and use it to advance their important work on lifesaving treatments. This is exactly why we made it freely available to the research community. https://
dpmd.ai/3YiMgmK -
Reference Papers for Llama 2 and DeBERTa Models
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3/3
Here are the papers for reference: Llama 2: Open Foundation and Fine-Tuned Chat Models: https://
arxiv.org/abs/2307.09288 DeBERTa: Decoding-enhanced BERT with Disentangled Attention: https://
arxiv.org/abs/2006.03654 -
DeBERTa-1.5B Outperforms Llama 2 on BoolQ Classification Task
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Interestingly, DeBERTa-1.5B (and encoder-only model) beats Llama 2 on BoolQ, which is a nice example that encoders still outperform large decoders on classification task. For fairness: The DeBERTa-1.5B model was likely finetuned on the training data 1/3
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PaddlePaddle Framework: Object Detection, Pose Estimation, Segmentation
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🎥New Videohttps://t.co/qJ6aEVc0o1
— Satya Mallick (@LearnOpenCV) 7 août 2023
Check out our awesome video, where we dive into the world of PaddlePaddle framework!
Discover the magic of object detection, pose estimation, and segmentation in PaddlePaddle using a Google Colab notebook! #PaddlePaddle #computervision #AI… pic.twitter.com/iQb3kOEAKQNew https://
youtube.com/watch?v=H_8nDp
2GRQU
… Check out our awesome video, where we dive into the world of PaddlePaddle framework!
Discover the magic of object detection, pose estimation, and segmentation in PaddlePaddle using a Google Colab notebook! #PaddlePaddle #computervision #AI -
Master TensorFlow, PyTorch, and scikit-learn through practical coding
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Explore libraries like #TensorFlow, #PyTorch, and scikit-learn. Hands-on #coding is key to bridging theory with real-world applications!
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Expression Language Composability Over Callbacks in Components
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because the expression language is more composable, callbacks may not be necessary as it may be easier just to run each component as its own for example, in the example above i took a stab at it and got: https://
gist.github.com/hwchase17/f93f
3043a5c9fe2b69e19e2674f80d19
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LLaMA2 Responsible Usage Guide Released by Meta
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LLaMA2 responsible usage guide(PDF): https://
scontent.fnbo1-1.fna.fbcdn.net/v/t39.8562-6/3
65271716_1020127512503290_6433760642443597145_n.pdf
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LLaMA2 Guide: Best Practices for LLM Development
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LLaMA2 came with this well-curated guide that includes best practices and resources for working with large language models, LLaMA in particular. This guide is a relevant resource for practitioners and developers(or basically anyone building with LLMs) as it covers important