lora
Using Low-rank adaptation to quickly fine-tune diffusion models. (by cloneofsimo)
llama.cpp
LLM inference in C/C++ (by ggerganov)
| lora | llama.cpp | |
|---|---|---|
| 83 | 777 | |
| 6,642 | 57,984 | |
| - | - | |
| 0.0 | 10.0 | |
| about 2 months ago | about 3 hours ago | |
| Jupyter Notebook | C++ | |
| Apache License 2.0 | MIT License |
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.
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.
-
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
-
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.
-
LoRA tuning in julia
No, it's a deep learning thing
-
What does Lora mean?
Low Rank Adaptation of Large Language Models.
-
[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.
-
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.
-
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...
-
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
llama.cpp
Posts with mentions or reviews of llama.cpp.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-05-07.
-
IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
-
Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
-
Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
-
Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
-
Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
When comparing lora and llama.cpp you can also consider the following projects:
stable-diffusion-webui - Stable Diffusion web UI
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
LyCORIS - Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion.
gpt4all - gpt4all: run open-source LLMs anywhere
sd_dreambooth_extension
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
ControlNet - Let us control diffusion models!
ggml - Tensor library for machine learning
sd-webui-additional-networks
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
lora vs stable-diffusion-webui
llama.cpp vs ollama
lora vs LyCORIS
llama.cpp vs gpt4all
lora vs sd_dreambooth_extension
llama.cpp vs text-generation-webui
lora vs kohya-trainer
llama.cpp vs GPTQ-for-LLaMa
lora vs ControlNet
llama.cpp vs ggml
lora vs sd-webui-additional-networks
llama.cpp vs alpaca.cpp