nn VS Basic-UI-for-GPT-J-6B-with-low-vram

Compare nn vs Basic-UI-for-GPT-J-6B-with-low-vram and see what are their differences.

nn

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠 (by lab-ml)
Deep Learning deep-learning-tutorial Pytorch Gan Transformers reinforcement-learning Optimizers neural-networks Transformer Machine Learning attention literate-programming
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nn.labml.ai
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Basic-UI-for-GPT-J-6B-with-low-vram

A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram. (by arrmansa)
gpt-neo Gpt Transformers
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nn Basic-UI-for-GPT-J-6B-with-low-vram
26 4
48,004 113
8.5% -
7.7 0.0
about 1 month ago over 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
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nn

Posts with mentions or reviews of nn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-09.

Basic-UI-for-GPT-J-6B-with-low-vram

Posts with mentions or reviews of Basic-UI-for-GPT-J-6B-with-low-vram. We have used some of these posts to build our list of alternatives and similar projects.
  • How to run this service with a local GPU?
    1 project | /r/PygmalionAI | 27 Jan 2023
    You need a lot of VRAM to run the AI models, scaling somewhat with the amount of parameters a model uses. The most advanced model Pygmalion has is 6 billion parameters, which requires a minimum of 16GB of VRAM to run locally at decent speeds. There are methods of running 6b locally on low VRAM machines as listed here: https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram but even then, the generations would be excruciatingly slow, and the lowest VRAM card used with this method has 6GB of VRAM.
  • Tesla M40 and GPT-J-6B
    1 project | /r/KoboldAI | 8 Aug 2021
    While waiting however I came across https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram which allows you to use some of system memory to run the model. I was able to get a version working with 2.7B on my 2060 6GB with KoboldAI. The github above has an error that prevents it from working (https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram/issues/1), but other than that it works.
  • How is any of this even possible?
    1 project | /r/GPT3 | 21 Jul 2021
    Just to add to this, there is a low VRAM version of GPT-J here (suggest 16GB RAM + 8GB GPU).
  • GPT-J 6B locally on my computer
    1 project | /r/KoboldAI | 25 Jun 2021
    I found this yesterday, is it somehow possible to use this with KoboldAI to run GPT-J on weaker graphics cards?

What are some alternatives?

When comparing nn and Basic-UI-for-GPT-J-6B-with-low-vram you can also consider the following projects:

GFPGAN-for-Video-SR - A colab notebook for video super resolution using GFPGAN

gpt-neo_dungeon - Colab notebooks to run a basic AI Dungeon clone using gpt-neo-2.7B

labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

functorch - functorch is JAX-like composable function transforms for PyTorch.

Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

ZoeDepth - Metric depth estimation from a single image

clip-italian - CLIP (Contrastive Language–Image Pre-training) for Italian

onnx-simplifier - Simplify your onnx model

pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

pytorch-generative - Easy generative modeling in PyTorch.

nn vs GFPGAN-for-Video-SR Basic-UI-for-GPT-J-6B-with-low-vram vs gpt-neo_dungeon nn vs labml Basic-UI-for-GPT-J-6B-with-low-vram vs adaptnlp nn vs functorch Basic-UI-for-GPT-J-6B-with-low-vram vs Behavior-Sequence-Transformer-Pytorch nn vs ZoeDepth Basic-UI-for-GPT-J-6B-with-low-vram vs clip-italian nn vs onnx-simplifier Basic-UI-for-GPT-J-6B-with-low-vram vs pytorch-sentiment-analysis nn vs Behavior-Sequence-Transformer-Pytorch Basic-UI-for-GPT-J-6B-with-low-vram vs pytorch-generative