lora
contriever
| lora | contriever | |
|---|---|---|
| 83 | 2 | |
| 6,642 | 476 | |
| - | - | |
| 0.0 | 10.0 | |
| about 2 months ago | about 1 year ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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lora
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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
contriever
- 100K Context Windows
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Will keyword (BM25, TD-IDF) be replaced for search by Neural Search?
We, humans, are preconditioned to be linear in our extrapolation (as opposed to exponential) thanks to our hunter ancestors (and FPS games!). It is very clear that the rate of advancement of Large Language Models is super-linear, if not exponential.
Hence, I indeed predict that keyword search will be completely supplanted in the next 5 years as a mechanism for search.
Of course we will still need to do lookups for ISBNs and generic ids, but that isn't keyword search, that is index lookup functionality.
Case in point: take a look at Meta Research's Contriever model (https://github.com/facebookresearch/contriever), which already matches keyword techniques in efficacy without any supervision.
This is only the beginning, come build the future with us, we see it very clearly :)
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
LyCORIS - Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion.
DocGPT - 💻📚💡 DoctorGPT provides advanced LLM prompting for PDFs and webpages. [Moved to: https://github.com/FeatureBaseDB/DoctorGPT]
sd_dreambooth_extension
finetune-transformer-lm - Code and model for the paper "Improving Language Understanding by Generative Pre-Training"
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
ControlNet - Let us control diffusion models!
sd-webui-additional-networks
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
stablediffusion - High-Resolution Image Synthesis with Latent Diffusion Models
peft - 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.