export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 NUM_GPUS=8 MODEL_COLDSTART_PATH="PATH_TO_SAVE_MODEL" FINAL_MODEL_PATH="PATH_TO_SAVE_MODEL" DATA_DIR="PATH_TO_DataScience-Instruct" INFERENCE_BACKEND="vllm" # Make sure you are in directory ./deepanalyze/SkyRL/skyrl-train/ python -m examples.deepanalyze.main_deepanalyze \ trainer.algorithm.advantage_estimator="grpo" \ trainer.epochs=1 \ data.train_data="[ \"${DATA_DIR}/RL/qa.parquet\", \"${DATA_DIR}/RL/datatask.parquet\", \"${DATA_DIR}/RL/reseach.parquet\" ]" \ trainer.policy.model.path="${MODEL_COLDSTART_PATH}" \ trainer.placement.colocate_all=true \ trainer.strategy="fsdp2" \ trainer.policy.fsdp_config.cpu_offload=true \ trainer.ref.fsdp_config.cpu_offload=true \ trainer.placement.policy_num_gpus_per_node=${NUM_GPUS} \ trainer.placement.ref_num_gpus_per_node=${NUM_GPUS} \ generator.num_inference_engines=${NUM_GPUS} \ generator.inference_engine_tensor_parallel_size=1 \ trainer.train_batch_size=256 \ trainer.micro_forward_batch_size_per_gpu=16 \ trainer.micro_train_batch_size_per_gpu=1 \ trainer.max_prompt_length=8000 \ generator.max_input_length=32768 \ generator.sampling_params.max_generate_length=32768 \ trainer.policy.optimizer_config.lr=5e-7 \ trainer.policy_mini_batch_size=256 \ trainer.algorithm.use_kl_loss=false \ generator.backend="${INFERENCE_BACKEND}" \ generator.run_engines_locally=true \ generator.weight_sync_backend="nccl" \ generator.async_engine=true \ generator.batched=false \ generator.use_conversation_multi_turn=false \ generator.n_samples_per_prompt=5 \ generator.gpu_memory_utilization=0.5 \ generator.max_turns=30 \ generator.sampling_params.temperature=0.0 \ generator.sampling_params.top_p=0.95 \ generator.sampling_params.stop_token_ids="[151676,151645]" \ environment.env_class="deepanalyze" \ environment.skyrl_gym.deepanalyze.workspace="${DATA_DIR}/RL/data/" \ trainer.logger="[\"console\",\"tensorboard\"]" \ trainer.project_name="deepanalyze" \ trainer.run_name="deepanalyze_0912" \ trainer.resume_mode="latest" \ trainer.ckpt_path="${FINAL_MODEL_PATH}/ckpt" \ trainer.export_path="${FINAL_MODEL_PATH}/export" \ trainer.eval_batch_size=8 \ trainer.eval_before_train=false \ trainer.eval_interval=-1 \ trainer.hf_save_interval=1 \ trainer.ckpt_interval=1