minGPT
gpt-2
minGPT | gpt-2 | |
---|---|---|
35 | 64 | |
18,875 | 21,146 | |
- | 1.1% | |
0.0 | 2.5 | |
7 days ago | 28 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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minGPT
- FLaNK AI Weekly for 29 April 2024
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Ask HN: Daily practices for building AI/ML skills?
minGPT (Karpathy): https://github.com/karpathy/minGPT
Next, some foundational textbooks for general ML and deep learning:
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[D] What are some examples of being clever with batching for training efficiency?
Language Model novice here. I was going through the README section of minGPT and read this line.
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LLM Visualization: 3D interactive model of a GPT-style LLM network running inference.
The first network displayed with working weights is a tiny such network, which sorts a small list of the letters A, B, and C. This is the demo example model from Andrej Karpathy's minGPT implementation.
- LLM Visualization
- Learn Machine Learning
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Facebook Prophet: library for generating forecasts from any time series data
Tried it once. Its promise is to take the dataset's seasonal trend into account, which makes sense for Facebook's original use case.
We ran it on such a dataset and found out that directly using https://github.com/karpathy/minGPT consistently gives a better result. So we ended up using the output of Prophet as an input feature to a neural network, but the result was not improved in any significant way.
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Tokenization of numerical series
Sure, im trying to regenerate a bunch of complex numbers based on their absolute value. So im trying to embed these absolute values and then using gpt model(probably mini gpt) try to recover the original comples numbers. There is a certain connection between these complex numbers and their order which im not capable of explaining yet. Im hoping the model would be capable of recognizing certain sequences of these absolute values and match them with the desired complex counterparts (by training the model).
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Anyone know of any articles on training a LLM from scratch on a single GPU?
minGPT (https://github.com/karpathy/minGPT)
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Understanding LLMs(to the best of our knowledge)
Check out minGPT and nanoGPT from Karpathy, he puts out some of the best machine learning tutorials and teaching content.
gpt-2
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What are LLMs? An intro into AI, models, tokens, parameters, weights, quantization and more
Medium models: Roughly between 1B to 10B parameters. This is where Mistral 7B, Phi-3, Gemma from Google DeepMind, and wizardlm2 sit. Fun fact: GPT 2 was a medium sized model, much smaller than its latest versions.
- Sam Altman is still trying to return as OpenAI CEO
- Build Personal ChatGPT Using Your Data
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Are the recent advancements in AI technology primarily driven by recent discoveries or the progress in hardware capabilities and the abundance of available data?
"Our model, called GPT-2 (a successor to GPT), was trained simply to predict the next word in 40GB of Internet text. Due to our concerns about malicious applications of the technology, we are not releasing the trained model. As an experiment in responsible disclosure, we are instead releasing a much smaller model for researchers to experiment with, as well as a technical paper. "
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BING IS NOW THE DEFAULT SEARCH FOR CHATGPT
They did release GPT-2 under the MIT License.
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Don Knuth Plays with ChatGPT
Did you arrive at this certainty through reading something other than what OpenAI has published? The document [0] that describes the training data for GPT-2 makes this assertion hilarious to me.
[0]: https://github.com/openai/gpt-2/blob/master/model_card.md#da...
- Was frustriert euch an der Nutzung oder der Diskussion um KI?
- The AI
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Help with pet project to learn - Running ChatGPT-2 at home
I made a clone of https://github.com/openai/gpt-2 on my local laptop
- По поводу опасности ИИ и предложений остановить разработки на 6 месяцев.
What are some alternatives?
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
dalle-mini - DALL·E Mini - Generate images from a text prompt
simpletransformers - Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Pytorch-Simple-Transformer - A simple transformer implementation without difficult syntax and extra bells and whistles.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
nn-zero-to-hero - Neural Networks: Zero to Hero
sentencepiece - Unsupervised text tokenizer for Neural Network-based text generation.
huggingface_hub - The official Python client for the Huggingface Hub.
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
tesla-model-y-checklist - Checklist for Tesla Model Y
mesh-transformer-jax - Model parallel transformers in JAX and Haiku