gpt-neo
mesh-transformer-jax
gpt-neo | mesh-transformer-jax | |
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82 | 52 | |
6,158 | 6,213 | |
- | - | |
7.3 | 0.0 | |
over 2 years ago | over 1 year ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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gpt-neo
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How Open is Generative AI? Part 2
By December 2020, EleutherAI had introduced The Pile, a comprehensive text dataset designed for training models. Subsequently, tech giants such as Microsoft, Meta, and Google used this dataset for training their models. In March 2021, they revealed GPT-Neo, an open-source model under Apache 2.0 license, which was unmatched in size at its launch. EleutherAI’s later projects include the release of GPT-J, a 6 billion parameter model, and GPT-NeoX, a 20 billion parameter model, unveiled in February 2022. Their work demonstrates the viability of high-quality open-source AI models.
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Creating an open source chat bot like ChatGPT for my own dataset without GPU?
Yeah, if that is your requirement you should definitely ignore chatterbot, as its older and probably not what your teacher wants. I'm looking at the gpt-neo docs right now: https://github.com/EleutherAI/gpt-neo
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Any real competitor to GPT-3 which is open source and downloadable?
3.) EleutherAI's GPT-Neo and GPT-NeoX: EleutherAI is an independent research organization that aims to promote open research in artificial intelligence. They have released GPT-Neo, an open-source language model based on the GPT architecture, and are developing GPT-NeoX, a highly-scalable GPT-like model. You can find more information on their GitHub repositories: GPT-Neo: https://github.com/EleutherAI/gpt-neo GPT-NeoX: https://github.com/EleutherAI/gpt-neox
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⚡ Neural - AI Code Generation for Vim
This is one of the first comprehensive plugins that has been rewritten to support multiple AI backends such as OpenAI GPT3+ and other custom sources in the future such as ChatGPT, GPT-J, GPT-neo and more.
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Looks like some Taliban fighters are getting burnt out working the 9-5 grind
GPT-Neo is newer than GPT-2 on the open source side of things. In my experience, it tends to give longer and more creative responses than GPT-2 but not on the level of GPT-3. I've not tried GPT-J or GPT-NeoX, but they're also open source and reportedly better than GPT-Neo (albeit less accessible).
- H3 - a new generative language models that outperforms GPT-Neo-2.7B with only *2* attention layers! In H3, the researchers replace attention with a new layer based on state space models (SSMs). With the right modifications, they find that it can outperform transformers.
- First Open Source Alternative to ChatGPT Has Arrived
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Where is the line for AI and where does ChatGPT stand?
Finally, yes-- it is trained via masked language modeling (text prediction). The approach has been fairly standard for years- the big difference with the GPT* models is the number of paramaters and volume of text-- we still haven't reached a ceiling with LLM parameters- they appear to keep improving with size. This training allows the model to learn a strong representation of language. Their training approach is published and open-source GPT* versions have already been made and released (https://github.com/EleutherAI/gpt-neo). However, the models are huge and can't be run locally for hobbyists. This gets at larger issues in democratization of ML.
- Using the GPT-3 AI Writer inside Obsidian(This is COOL)
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Teaser trailer for "The Diary of Sisyphus" (2023), the world's first feature film written by an artificial intelligence (GPT-NEO) and produced Briefcase Films, my indie film studio based in Northern Italy
- GPT-Neo 2.7B, released Mar/2021, and unmaintained/unsupported as of Aug/2021? or;
mesh-transformer-jax
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Large Language Models: Compairing Gen2/Gen3 Models (GPT-3, GPT-J, MT5 and More)
GPT-J is a LLM case study with two goals: Training a LLM with a data source containing unique material, and using the training frameworkMesh Transformer JAX to achieve a high training efficiency through parallelization. There is no research paper about GPT-J, but on its GitHub pages, the model, different checkpoints, and the complete source code for training is given.
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[R] Parallel Attention and Feed-Forward Net Design for Pre-training and Inference on Transformers
This idea has already been proposed in ViT-22B and GPT-J-6B.
- Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
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[D] An Instruct Version Of GPT-J Using Stanford Alpaca's Dataset
Sure. Here's the repo I used for the fine-tuning: https://github.com/kingoflolz/mesh-transformer-jax. I used 5 epochs, and appart from that I kept the default parameters in the repo.
- Boss wants me to use ChatGPT for work, but I refuse to input my personal phone number. Any advice?
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Let's build GPT: from scratch, in code, spelled out by Andrej Karpathy
You can skip to step 4 using something like GPT-J as far as I understand: https://github.com/kingoflolz/mesh-transformer-jax#links
The pretrained model is already available.
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Best coding model?
The Github repo suggests it's possible you can change the number of checkpoints to make it run on a GPU.
- Ask HN: What language models can I fine-tune at home?
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selfhosted/ open-source ChatGPT alternative?
GPT-J, which uses mesh-transformer-jax: https://github.com/kingoflolz/mesh-transformer-jax
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GPT-J, an open-source alternative to GPT-3
They hinted at it in the screenshot, but the goods are linked from the https://6b.eleuther.ai page: https://github.com/kingoflolz/mesh-transformer-jax#gpt-j-6b (Apache 2)
What are some alternatives?
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
tensorflow - An Open Source Machine Learning Framework for Everyone
openchat - OpenChat: Easy to use opensource chatting framework via neural networks
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
KoboldAI-Client
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
alpaca-lora - Instruct-tune LLaMA on consumer hardware
lm-evaluation-harness - A framework for few-shot evaluation of language models.
Finetune_LLMs - Repo for fine-tuning Casual LLMs