SVGDreamer
[CVPR 2024] Official implementation for "SVGDreamer: Text Guided SVG Generation with Diffusion Model" https://arxiv.org/abs/2312.16476 (by ximinng)
peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning. (by huggingface)
| SVGDreamer | peft | |
|---|---|---|
| 1 | 26 | |
| 124 | 14,597 | |
| - | 5.6% | |
| 7.6 | 9.7 | |
| 25 days ago | 4 days ago | |
| Python | Python | |
| MIT License | 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.
SVGDreamer
Posts with mentions or reviews of SVGDreamer.
We have used some of these posts to build our list of alternatives
and similar projects.
peft
Posts with mentions or reviews of peft.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-05.
- LoftQ: LoRA-fine-tuning-aware Quantization
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Fine Tuning Mistral 7B on Magic the Gathering Draft
There is not a lot of great content out there making this clear, but basically all that matters for basic fine tuning is how much VRAM you have -- since the 3090 / 4090 have 24GB VRAM they're both pretty decent fine tuning chips. I think you could probably fine-tune a model up to ~13B parameters on one of them with PEFT (https://github.com/huggingface/peft)
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Whisper prompt tuning
Hi everyone. Recently I've been looking into the PEFT library (https://github.com/huggingface/peft) and I was wondering if it would be possible to do prompt tuning with OpenAI's Whisper model. They have an example notebook for tuning Whisper with LoRA (https://colab.research.google.com/drive/1vhF8yueFqha3Y3CpTHN6q9EVcII9EYzs?usp=sharing) but I'm not sure how to go about changing it to use prompt tuning instead.
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Code Llama - The Hugging Face Edition
In the coming days, we'll work on sharing scripts to train models, optimizations for on-device inference, even nicer demos (and for more powerful models), and more. Feel free to like our GitHub repos (transformers, peft, accelerate). Enjoy!
- PEFT 0.5 supports fine-tuning GPTQ models
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Exploding loss when trying to train OpenOrca-Platypus2-13B
image
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[D] Is there a difference between p-tuning and prefix tuning ?
I discussed part of this here: https://github.com/huggingface/peft/issues/123
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How does using QLoRAs when running Llama on CPU work?
It seems like the merge_and_unload function in this PEFT script might be what they are referring to: https://github.com/huggingface/peft/blob/main/src/peft/tuners/lora.py
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How to merge the two weights into a single weight?
To obtain the original llama model, one may refer to this doc. To merge a lora model with a base model, one may refer to PEFT or use the merge script provided by LMFlow.
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[D] [LoRA + weight merge every N step] for pre-training?
you could use a callback, like show here, https://github.com/huggingface/peft/issues/286 and call code to merge them here.
What are some alternatives?
When comparing SVGDreamer and peft you can also consider the following projects:
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
alpaca-lora - Instruct-tune LLaMA on consumer hardware
dalai - The simplest way to run LLaMA on your local machine
mlc-llm - Universal LLM Deployment Engine with ML Compilation
minLoRA - minLoRA: a minimal PyTorch library that allows you to apply LoRA to any PyTorch model.
lamini
simple-llm-finetuner - Simple UI for LLM Model Finetuning
alpaca_lora_4bit
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
SwapCudaVersionWindows - How to swap/switch CUDA versions on Windows
PorousMediaLab - PorousMediaLab - toolbox for batch and 1D reactive transport modelling