bupticybee

GPU is good at doing parallel task that in nature is the same. So it fit perfectly in CFR context. CFR is basically doing a lot of similar work across nodes. So if you implememnt a cuda kernel for regret matching, it will accelerate the solving process a lot.

I made this project to combine advantages of alpaca-lora and fastchat.

I opensourced everything, including the share GPT dataset I used for training, model ,and training script.

I hope this project would allow people with lower-end GPU have a chance to train chatGPT-like LLM.

Really fun stuff, perhaps you should use a computer screen instead of producing one

After two weeks of hardwork, TexasHoldemSolverJava 0.2.0 is complete. A gui is created. Now it's a fully functional solver. It supports texas holdem and shortdeck. Most important, It's totally free and opensourced (piosolver costs hunderds of dollars). I really hope this project can bring some small change to the texas holdem community.

To be simple, python is not fast enought for solving, java is not fast enough for coding. So my solution is build prototype with python and transfer the code to java.