LECO
Low-rank adaptation for Erasing COncepts from diffusion models. (by p1atdev)
lora
Using Low-rank adaptation to quickly fine-tune diffusion models. (by cloneofsimo)
| LECO | lora | |
|---|---|---|
| 1 | 83 | |
| 289 | 6,650 | |
| - | - | |
| 7.8 | 0.0 | |
| 4 months ago | 2 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
LECO
Posts with mentions or reviews of LECO.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-16.
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Unified Concept Editing in Diffusion Models
Editing models in seconds. This is an upgrade to the lora sliders (https://erasing.baulab.info and https://github.com/p1atdev/LECO) but faster training with no damage to the model prior knowledge! Check out their code: https://github.com/rohitgandikota/unified-concept-editing
lora
Posts with mentions or reviews of lora.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-07.
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You can now train a 70B language model at home
Diffusion unet has an "extended" version nowadays that applies to the resnet part as well as the cross-attention: https://github.com/cloneofsimo/lora
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How it feels right now
Absolutely. But that doesn't matter because you only have to train it at scale, once. There are papers released already that show it's possible to update weights in small sections. You won't have to wait for the next monolithic LLM to drop to get up to date information. It will start to learn in bits and pieces.
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LoRA tuning in julia
No, it's a deep learning thing
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What does Lora mean?
Low Rank Adaptation of Large Language Models.
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[D] An ELI5 explanation for LoRA - Low-Rank Adaptation.
Recently, I have seen the LoRA technique (Low-Rank Adaptation of Large Language Models) as a popular method for fine-tuning LLMs and other models.
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Combining LoRA, Retro, and Large Language Models for Efficient Knowledge Retrieval and Retention
Enter LoRA, a method proposed for adapting pre-trained models to specific tasks[2]. By freezing pre-trained model weights and injecting trainable rank decomposition matrices into the transformer architecture, LoRA can reduce the number of trainable parameters and the GPU memory requirement, making the adaptation of LLMs for downstream tasks more feasible.
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100K Context Windows
Open-source LLM projects have largely solved this using Low-Rank Adaptation of Large Language Models (LoRA): https://arxiv.org/abs/2106.09685
Apparently an RTX 4090 running overnight is sufficient to produce a fine-tuned model that can spit out new Harry Potter stories, or whatever...
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President Biden meets with AI CEOs at the White House amid ethical criticism
Alpaca was trained for $600 ($100 for the smaller model) and offers outputs competitive with ChatGTP. https://arxiv.org/abs/2106.09685
- LoRA: Low-Rank Adaptation of Large Language Models
- LORA: Low-Rank Adaptation of Large Language Models