tutorial(training): Add a minimal example with trl (#473)

* v0

* 2 gpu setup

* improve parsing from yaml

* update yaml dataset example

* remove restriction on flash attn

* more comments

* first version of the readme

* pin torch

* simplify requirements

* just flash attn

* use set env instead

* simpler set env

* readme

* add wandb project to setup

* update template

* update model id

* post init to capture the config and weight

* extract metadata

* update config

* update dataset config

* move env for wandb project

* pre-commit

* remove qwen-math from training

* more instructions

* unused import

* remove trl old

* warmup ratio

* warmup ratio

* change model id

* change model_id

* add info about CUDA_VISIBLE_DEVICES

training/qwen-math/scripts/set/set_env.sh

@@ -1,39 +0,0 @@
-#!/bin/bash
-# python 3.10 + cuda 11.8.0
-# the execution order the following commands matter
-
-export MKL_NUM_THREADS=1
-export NUMEXPR_NUM_THREADS=1
-export OPENBLAS_NUM_THREADS=1
-export OMP_NUM_THREADS=1
-
-conda clean -a -y
-mamba clean -a -y
-pip install --upgrade pip
-pip cache purge
-
-# cuda, gcc/g++, torch
-# mamba install cuda -c nvidia/label/cuda-11.8.0 -y
-# mamba install gcc gxx -c conda-forge -y
-pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu118
-
-# xformers
-pip install xformers==0.0.28.post3 --index-url https://download.pytorch.org/whl/cu118
-
-# vLLM pre-compiled with CUDA 11.8
-pip install https://github.com/vllm-project/vllm/releases/download/v0.7.2/vllm-0.7.2+cu118-cp38-abi3-manylinux1_x86_64.whl
-
-pip install deepspeed
-pip install flash-attn==2.7.3 --no-build-isolation
-pip install peft
-
-pip install "trl==0.15.2"
-pip install latex2sympy2_extended
-pip install "math_verify==0.5.2"
-pip install word2number
-pip install scipy
-
-pip install wandb
-pip install plotly
-pip install matplotlib
-pip install seaborn