jalammar

5 ms·

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by jalammar 5y ago
Hi HN, This is the first in a series of articles I'm writing to introduce devs to practical applications of large NLP language models (for text generations like GPT and for language understanding like BERT). I have been connecting the
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A Visual Intro to Large Language Models(docs.cohere.ai)
50 points by jalammar 5y ago|2 comments
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by jalammar 5y ago
It's widely used in recommenders based on embeddings. See: https://github.com/spotify/annoy https://github.com/facebookresearch/faiss
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by jalammar 5y ago
Hi HN, I created this cheat sheet and video as high-level guidance to the major categories of ML explainability research and techniques. It's an area I've been working in the last year and this is how I synthesized the lay of the
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Show HN: Explainable AI Cheat Sheet(ex.pegg.io)
2 points by jalammar 5y ago|1 comments
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by jalammar 5y ago
I wouldn't trust any model to generate text for customers yet. Not even the largest GPT3. There are no guarantees on what they will output and could be damaging to your business. You're better off either: 1- Defining common "
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by jalammar 5y ago
Hugging Face has that service https://huggingface.co/pricing
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by jalammar 6y ago
I didn't come across one yet personally
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by jalammar 6y ago
Hello HN, author here. Language models are absolutely fascinating tools. I believe it would pay for software engineers to have a sense of their capabilities and how they function. The article showcases a few views to expose the inner workin
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Finding the Words to Say: Hidden State Visualizations for Language Models(jalammar.github.io)
55 points by jalammar 6y ago|4 comments
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by jalammar 6y ago
Hey, I feel you! I'm an intuitive learner as well. I wouldn't have been able to learn much in ML if it weren't for people who write and visualize and make the methods accessible to non-experts. In my case, as with many others
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by jalammar 6y ago
I actually started with PCA. But NMF proved more understandable since negative dimensions in PCA are hard to interpret. I didn't consider UMAP, but would be interested to see how it performs here. It should be easy, yeah. for NMF, the
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by jalammar 6y ago
Interesting. Thanks for sharing your notes on the higher layers. Allow me to repost that to the discussion board on github. I do get your point on interpretation. This work is just a starting point. I'm curious to arrive at ways to aut
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by jalammar 6y ago
These are AI explanation methods. They belong to the toolbox which would include LIME, Shapley values...etc. Input saliency is a gradient-based explanation method.
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by jalammar 6y ago
Wonderful! Thanks! I am curious about those recent O(L) attention transformers (see slide 106 of http://gabrielilharco.com/publications/EMNLP_2020_Tutorial__... ). If these methods are converging towards a new self-atte
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by jalammar 6y ago
I'd love to look at your group's visualizations! Is it a private repo? because the link doesn't open up. It never stops to blow my mind that we can represent words and concepts in vectors of numbers. Thanks for your kind word
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by jalammar 6y ago
Thanks! Please let me know if you have any feedback!
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by jalammar 6y ago
What I found most fascinating is identifying neuron firing patterns corresponding to linguistic properties: e.g. groups of neurons that fire in response to verbs, or pronounds. Scroll down to "Factorizing Activations of a Single Layer&
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by jalammar 6y ago
Thank you!
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by jalammar 6y ago
Hi HN, Author here. I had been fascinated with Andrej Karpathy's article ( https://karpathy.github.io/2015/05/21/rnn-effectiveness/ ) -- especially where it shows neurons being activated in response t
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Show HN: Ecco – See what your NLP language model is “thinking”(eccox.io)
185 points by jalammar 6y ago|34 comments
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Interfaces for Explaining Transformer Language Models(jalammar.github.io)
2 points by jalammar 6y ago|0 comments
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by jalammar 6y ago
Apple Keynote
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by jalammar 6y ago
Author here. Thank you. I feel an important element of this type of writing is what complexity to show and what to hide at different points. "Magic" is just to say "don't worry about the contents of this box yet, we&#x27
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How GPT3 Works. Visuals and Animations(twitter.com)
2 points by jalammar 6y ago|0 comments
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by jalammar 6y ago
Hi HN, This is the first video in a series where I gently explain AI/ML with an emphasis on applications rather than the math/stats/algorithms. It's meant for the general public, but I hope it helps the practitioners und
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Jay's Visual Intro to AI (video focusing on business applications)(youtube.com)
1 points by jalammar 6y ago|1 comments
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by jalammar 7y ago
Hi HN, author here. I'm hoping for this tutorial to be the gentlest way for you to get your first exposure to the BERT model. I hope you find it useful. All feedback/corrections are welcomed.
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A Visual Guide to Using BERT for the First Time(jalammar.github.io)
1 points by jalammar 7y ago|1 comments
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The Illustrated GPT-2 (Visualizing Transformer Language Models)(jalammar.github.io)
2 points by jalammar 7y ago|0 comments

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