labml
nn
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labml | nn | |
---|---|---|
23 | 26 | |
1,867 | 48,004 | |
4.3% | 8.5% | |
9.7 | 7.7 | |
3 days ago | about 1 month ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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.
labml
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Creating stickers using SD with img2img
Used the PromptArt app by labml.ai to generate a sticker of an image I took from my iPhone. The results are amazing.
- [D] Why doesnโt your team use an experiment tracking tool?
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Probe PyTorch models
๐ป Github
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[P] Probe PyTorch models
๐งโ๐ซ Demo that extracts attention maps of BERT
- Show HN: Probe PyTorch Models
- [D] How do you guys tune hyperparameters, when a single training run takes a long time (days to weeks)?
- Machine Learning Best Practices
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[D] Machine Learning Best Practices
from github
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[P] Annotated deep learning paper implementations
labmlai/labml is a set of tools (tracking experiments, configurations, a bunch of helpers) we coded to ease our ML work (which later improved and open sourced). So we use it in all our projects because it makes things easier for us.
- React's UI State Model vs. Vanilla JavaScript
nn
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Can't remember name of website that has explanations side-by-side with code
Hey are you talking about https://nn.labml.ai/ ?
- [D] Recent ML papers to implement from scratch
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[P] GPT-NeoX inference with LLM.int8() on 24GB GPU
Implementation & LM Eval Harness Results
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[P] Fine-tuned the GPT-Neox Model to Generate Quotes
Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/neox
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Best resources to learn recent transformer papers and stay updated [D]
Regarding implementations this helps me: https://nn.labml.ai/
- Introductory papers to implement
- How to convert research papers to code?
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[D] How to convert papers to code?
Dunno if this is directly helpful, but this website has implementation with the math side by side https://nn.labml.ai/
- [D] Looking for open source projects to contribute
- Resource for papers explanation
What are some alternatives?
guildai - Experiment tracking, ML developer tools
GFPGAN-for-Video-SR - A colab notebook for video super resolution using GFPGAN
Practical_RL - A course in reinforcement learning in the wild
functorch - functorch is JAX-like composable function transforms for PyTorch.
Deep-Learning-Push-Up-Counter - Deep Learning approach to count the number of repetitions in a video of push ups or pull ups.
ZoeDepth - Metric depth estimation from a single image
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
onnx-simplifier - Simplify your onnx model
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light๐ก image enhancement
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.
Lottery_Ticket_Hypothesis-TensorFlow_2 - Implementing "The Lottery Ticket Hypothesis" paper by "Jonathan Frankle, Michael Carbin"
Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf