Takeaways from hundreds of LLM finetuning experiments with LoRA (lightning.ai)

Screenshot of lightning.ai: Takeaways from hundreds of LLM finetuning experiments with LoRA

First screen, captured 3 years ago.

Looks similar

Screenshot of lightning.ai: Finetuning LLMs on a Single GPU Using Gradient Accumulation

Finetuning LLMs on a Single GPU Using Gradient Accumulation (lightning.ai)

76 points by ashvardanian 3 years ago | 2 comments

Screenshot of lightning.ai: How to Finetune GPT-Like Large Language Models on a Custom Dataset

How to Finetune GPT-Like Large Language Models on a Custom Dataset (lightning.ai)

465 points by T-A 3 years ago | 118 comments

Lightning AI blog tutorial by Aniket Maurya explaining how to finetune GPT-like large language models on a custom dataset.

llm-finetuning large-language-models lightning-ai gpt

Screenshot of blog.kasperjunge.com: The Most Underrated Application of LLMs

The Most Underrated Application of LLMs (blog.kasperjunge.com)

56 points by juunge 3 years ago | 22 comments

Screenshot of efraingaray.com: TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14 (efraingaray.com)

21 points by EfrainGaray 28 days ago | 9 comments

Blog post benchmarking TabPFN and TabICL foundation models against tuned XGBoost on fourteen tabular datasets, finding the no-training models won all fourteen.

tabpfn tabicl xgboost tabular-data

Screenshot of nuenki.app: Experimentation Matters: Why Nuenki isn't using pairwise evaluations

Experimentation Matters: Why Nuenki isn't using pairwise evaluations (nuenki.app)

4 points by Alex-Programs 1 year ago | 0 comments

Screenshot of uds5501.github.io: OpenGL to WASM, learning from my mistakes

OpenGL to WASM, learning from my mistakes (uds5501.github.io)

71 points by uds5501 1 year ago | 18 comments

Looks similar

Finetuning LLMs on a Single GPU Using Gradient Accumulation(lightning.ai)

How to Finetune GPT-Like Large Language Models on a Custom Dataset(lightning.ai)

The Most Underrated Application of LLMs(blog.kasperjunge.com)

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14(efraingaray.com)

Experimentation Matters: Why Nuenki isn't using pairwise evaluations(nuenki.app)

OpenGL to WASM, learning from my mistakes(uds5501.github.io)