From 96c65bc05aa2d00119e3f14ccea6b96be807b3d1 Mon Sep 17 00:00:00 2001 From: Bruce Yang ByFinTech Date: Fri, 20 Oct 2023 10:10:22 +0800 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 5ff605f..9136191 100644 --- a/README.md +++ b/README.md @@ -96,7 +96,7 @@ The datasets we used, and the **multi-task financial LLMs** models are available **Cost per GPU hour.** For **A100 GPUs**, the AWS p4d.24xlarge instance, equipped with 8 A100 GPUs is used as a benchmark to estimate the costs. Note that BloombergGPT also used p4d.24xlarge As of July 11, 2023, the hourly rate for this instance stands at $32.773. Consequently, the estimated cost per GPU hour comes to $32.77 divided by 8, resulting in approximately **$4.10**. With this value as the reference unit price (1 GPU hour). **BloombergGPT estimated cost= 512 x 53 x 24 = 651,264 GPU hours x $4.10 = $2,670,182.40**. For **RTX 3090**, we assume its cost per hour is approximately **$1.0**, which is actually much higher than available GPUs from platforms like vast.ai. * Reproduce the results by running [benchmarks](./fingpt/FinGPT_v3/benchmark/benchmarks.ipynb), and the detailed tutorial is on the way. - * Finetune your own FinGPT v3 model with the LoRA method on only an RTX 3090 with this [notebook](./fingpt/FinGPT_v3/training_8bit/train.ipynb) in 8bit or this [notebook](./fingpt/FinGPT_v3/training_int4/train.ipynb) in int4 (QLoRA) + * Finetune your own FinGPT v3 model with the LoRA method on only an RTX 3090 with this [notebook](./fingpt/FinGPT_v3/training_8bit/train_Llama2_13B.ipynb) in 8bit or this [notebook](./fingpt/FinGPT_v3/training_int4/train.ipynb) in int4 (QLoRA) * [FinGPT V1](./fingpt) + **FinGPT by finetuning ChatGLM2 / Llama2 with LoRA with the market-labeled data for the Chinese Market**