gatsby-starter-lumen
transformers
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gatsby-starter-lumen | transformers | |
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3 | 175 | |
1,976 | 125,021 | |
- | 3.1% | |
9.9 | 10.0 | |
about 17 hours ago | about 14 hours ago | |
TypeScript | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gatsby-starter-lumen
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Building a 11ty website in a weekend
Until now, my personal website was using a Gatsby with a beautiful template named Lumen. Since I don't want to re-write my website every year to follow the latest trend in React world and since I couldn't change much without learning the framework, I've decided to switch to something else. Many static site generators needs several days or weeks to be mastered, so I went for the simpler solution to be able to build the first version of my website in a weekend: 11ty.
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[TASK] Help needed with SSL_ERROR_ILLEGAL_PARAMETER_ALERT error on React website
The blog is based on this theme: https://github.com/alxshelepenok/gatsby-starter-lumen
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Growth Hacking Github - How to Get Github Stars
For my tailwind nextjs template, I did not want to restrict it to only Nextjs projects using Tailwind CSS but rather look at other blog templates. Other similar templates in my comparison list include Gatsby Starter Lumen or Hugo Coder which tells me that a realistic upper bound for a personal portfolio template project is about 1.5k stars.
transformers
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Maxtext: A simple, performant and scalable Jax LLM
Is t5x an encoder/decoder architecture?
Some more general options.
The Flax ecosystem
https://github.com/google/flax?tab=readme-ov-file
or dm-haiku
https://github.com/google-deepmind/dm-haiku
were some of the best developed communities in the Jax AI field
Perhaps the “trax” repo? https://github.com/google/trax
Some HF examples https://github.com/huggingface/transformers/tree/main/exampl...
Sadly it seems much of the work is proprietary these days, but one example could be Grok-1, if you customize the details. https://github.com/xai-org/grok-1/blob/main/run.py
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Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
The HuggingFace transformers library already has support for a similar method called prompt lookup decoding that uses the existing context to generate an ngram model: https://github.com/huggingface/transformers/issues/27722
I don't think it would be that hard to switch it out for a pretrained ngram model.
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AI enthusiasm #6 - Finetune any LLM you want💡
Most of this tutorial is based on Hugging Face course about Transformers and on Niels Rogge's Transformers tutorials: make sure to check their work and give them a star on GitHub, if you please ❤️
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Schedule-Free Learning – A New Way to Train
* Superconvergence + LR range finder + Fast AI's Ranger21 optimizer was the goto optimizer for CNNs, and worked fabulously well, but on transformers, the learning rate range finder sadi 1e-3 was the best, whilst 1e-5 was better. However, the 1 cycle learning rate stuck. https://github.com/huggingface/transformers/issues/16013
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Gemma doesn't suck anymore – 8 bug fixes
Thanks! :) I'm pushing them into transformers, pytorch-gemma and collabing with the Gemma team to resolve all the issues :)
The RoPE fix should already be in transformers 4.38.2: https://github.com/huggingface/transformers/pull/29285
My main PR for transformers which fixes most of the issues (some still left): https://github.com/huggingface/transformers/pull/29402
- HuggingFace Transformers: Qwen2
- HuggingFace Transformers Release v4.36: Mixtral, Llava/BakLlava, SeamlessM4T v2
- HuggingFace: Support for the Mixtral Moe
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Paris-Based Startup and OpenAI Competitor Mistral AI Valued at $2B
If you want to tinker with the architecture Hugging Face has a FOSS implementation in transformers: https://github.com/huggingface/transformers/blob/main/src/tr...
If you want to reproduce the training pipeline, you couldn't do that even if you wanted to because you don't have access to thousands of A100s.
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Fail to reproduce the same evaluation metrics score during inference.
I am aware that using mixed precision reduces the stability of weight and there will be little consistency but don't expect it to be this much. I have attached the graph of evaluation metrics. If someone can give me some insight into this issue, that would be great.
What are some alternatives?
tailwind-nextjs-starter-blog - This is a Next.js, Tailwind CSS blogging starter template. Comes out of the box configured with the latest technologies to make technical writing a breeze. Easily configurable and customizable. Perfect as a replacement to existing Jekyll and Hugo individual blogs.
fairseq - Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
rick-and-morty-api-site - The Rick and Morty API site
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
trailing-slash-guide - Understand and fix your static website trailing slash issues!
llama - Inference code for Llama models
schnack - 🗣️ Simple self-hosted node app for Disqus-like drop-in commenting on static websites
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
Gatsby - The best React-based framework with performance, scalability and security built in.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
blog - :thought_balloon: Maybe some extraterrestrial will read this someday.
huggingface_hub - The official Python client for the Huggingface Hub.