labml.ai @labmlai
📝 Annotated paper implementations https://t.co/qeO4UTbrJ3 labml.ai Joined December 2020-
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Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking arxiv.org/abs/2403.09629 It trains language models to generate rationales at each token to explain future text, to improve their predictions. 🧵👇
Hoping to add more paper implementations. Any suggestions?
Hoping to add more paper implementations. Any suggestions?
✨ 40k stars for our annotated research paper implementation project. Thanks for the love! Annotated code: nn.labml.ai Github: github.com/labmlai/annota…
Annotated @PyTorch implementation of U-Net 📝 Code nn.labml.ai/unet/index.html 🖥 Github github.com/labmlai/annota… 📎 Paper papers.labml.ai/paper/1505.045… U-Net is a symmetric U shaped model with conv layers. Used for modeling feature map->feature map data such as segmentation.
🎉 You can now click on maths expressions to highlight them across the page! Annotated deep learning paper implementations in @PyTorch: 📝 nn.labml.ai We just added this feature so let us know if you come across any bugs and have thoughts for improvements.
Annotated PyTorch papers! 🔥 @labmlai has the best resources for learning how to really implement ideas This is a no-nonsense website with a side-by-side implementation of papers in @PyTorch The transformers section is my fav: nn.labml.ai/index.html
Trending repository of the day 📈 annotated_deep_learning_paper_implementations by @labmlai 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; in... Main language: Jupyter Notebook Last 24h: 633 ⭐ Total: 29175 ⭐️ github.com/labmlai/annota…
🥳 Our "Annotated Research Paper Implementations" Github repo reached 25,000 stars! github.com/labmlai/annota… It has over 50 paper implementations. Thank you everyone for the support!
Apologies for the inconvenience caused by the interruption in our tweets featuring popular research papers on papers.labml.ai. We regret to inform you that we have encountered issues with our previous Twitter data collection app, which has been discontinued due to new…
Proximal Policy Optimization is the RL technique often used for RLHF. @labmlai has provided a PPO implementation with equations and explanation side-by-side. Check it out here → nn.labml.ai/rl/ppo/index.h…
Updated the GeoV-9b model weights at 80 billion tokens trained by @gharik 📀 huggingface.co/GeoV/GeoV-9b We evaluated the model with @AiEleuther LM eval harness. Results 👉 github.com/geov-ai/geov/b… We'll continue to upload weights and evaluate the model as training progresses.
Updated the GeoV-9b model weights at 80 billion tokens trained by @gharik 📀 huggingface.co/GeoV/GeoV-9b We evaluated the model with @AiEleuther LM eval harness. Results 👉 github.com/geov-ai/geov/b… We'll continue to upload weights and evaluate the model as training progresses.
Updated the GeoV-9b model weights at 74 billion tokens trained @gharik 📀 huggingface.co/GeoV/GeoV-9b And we are working on adding it to @huggingface transformers github.com/huggingface/tr…
Updated the GeoV-9b model weights at 74 billion tokens trained @gharik 📀 huggingface.co/GeoV/GeoV-9b And we are working on adding it to @huggingface transformers github.com/huggingface/tr…
RoPER does better than rotational embeddings (RoPE) on algorithmic tasks and works a little better in our initial tests on language modeling too. Here is the RoPER paper (research.labml.ai/RoPER.html) and the annotated implementation (nn.labml.ai/transformers/r…).
RoPER does better than rotational embeddings (RoPE) on algorithmic tasks and works a little better in our initial tests on language modeling too. Here is the RoPER paper (research.labml.ai/RoPER.html) and the annotated implementation (nn.labml.ai/transformers/r…).
GeoV-9b language model @gharik & @labml is releasing a 9 billion parameter LM with open licenses to be useful in a variety of settings. The current version is trained for ~69B tokens and they will continue training for 300B tokens. 📗 Google Colab notebook:…
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Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking arxiv.org/abs/2403.09629 It trains language models to generate rationales at each token to explain future text, to improve their predictions. 🧵👇
Worked with @ericzelikman @EchoShao8899 @vpj @nickhaber @noahdgoodman on this awesome paper to train LLMs to reason before they speak, from data at large. arxiv.org/abs/2403.09629
Hoping to add more paper implementations. Any suggestions?
✨ 40k stars for our annotated research paper implementation project. Thanks for the love! Annotated code: nn.labml.ai Github: github.com/labmlai/annota…
Nice work!
⏳ A simple @PyTorch implementation of hourglass transformer with side-by-side notes from the paper Hierarchical Transformers Are More Efficient Language Models 📝 code/notes nn.labml.ai/transformers/h… 📎 paper papers.labml.ai/paper/768de41e… 🧵👇
🎉 You can now click on maths expressions to highlight them across the page! Annotated deep learning paper implementations in @PyTorch: 📝 nn.labml.ai We just added this feature so let us know if you come across any bugs and have thoughts for improvements.
@bhutanisanyam1 @labmlai @PyTorch Glad you liked it! Thanks for sharinf
Annotated PyTorch papers! 🔥 @labmlai has the best resources for learning how to really implement ideas This is a no-nonsense website with a side-by-side implementation of papers in @PyTorch The transformers section is my fav: nn.labml.ai/index.html
Super impressed by @labmlai! One of the best ways to understand papers.
@hnipun1 @labmlai @papers_daily I understand. The Twitter API is indeed quite expensive. I appreciate your persistence, and I hope it continues to improve. Thank you.🥳
Ek hi Dil hai kitni baar jeetoge? Translation: I've just one heart, how many times do you wanna win it?
🥳 Our "Annotated Research Paper Implementations" reached 30,000 stars on Github! Thank you! github.com/labmlai/annota… It has 60 paper implementations in @PyTorch 📝 Here's the code with side-by-side notes: nn.labml.ai
catching up with the latest research after a break is easy thanks to @labmlai 😀 papers.labml.ai/papers/recent/
Trending repository of the day 📈 annotated_deep_learning_paper_implementations by @labmlai 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; in... Main language: Jupyter Notebook Last 24h: 633 ⭐ Total: 29175 ⭐️ github.com/labmlai/annota…
Apologies for the inconvenience caused by the interruption in our tweets featuring popular research papers on papers.labml.ai. We regret to inform you that we have encountered issues with our previous Twitter data collection app, which has been discontinued due to new…
@iScienceLuvr @labmlai Thanks for sharing. Glad you found it useful. PPO was the first annotated paper implementation.
I'm trying to better understand how PPO works, and I figured I'd check to see if this website has an implementation. It has implementations of many papers, from transformers to diffusion models, with side-by-side equations and explanations. Such an awesome resource!
Proximal Policy Optimization is the RL technique often used for RLHF. @labmlai has provided a PPO implementation with equations and explanation side-by-side. Check it out here → nn.labml.ai/rl/ppo/index.h…
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning ai.papers.bar/paper/49552082… Table-based reasoning has shown remarkable progress in combining deep models with... 🧵 👇
@vgoklani_ai @labmlai @_akhaliq @AiEleuther Will try to do those things may take a bit.
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