add gptoss grpo example script (#3212)

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Adding a script to run gpt-oss 20B model with VeRL. 


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# Add code snippet or script demonstrating how to use this
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Co-authored-by: RichardW <richard.junwang@bytedance.com>
Co-authored-by: GeLee-Q  <leege233@gmail.com>
Co-authored-by: zhaochenyang20  <zhaochen20@outlook.com>

Author: 4 people

examples/grpo_trainer/run_gptoss_20b.sh

@@ -0,0 +1,94 @@
+#!/bin/bash
+
+# install flashinfer
+cd $HOME
+git clone https://github.com/flashinfer-ai/flashinfer.git --recursive
+cd flashinfer
+python -m pip install -v .
+
+# install sglang
+cd $HOME
+git fetch origin pull/9379/head:fix_weight_loading
+cd $HOME/sglang
+git checkout fix_weight_loading
+pip install --upgrade pip
+pip install -e "python[all]"
+
+pip install peft
+pip install transformers -U
+pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp311-cp311-linux_x86_64.whl
+pip install numpy==1.26.4
+
+
+cat > get_model.py << EOF
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, Mxfp4Config
+
+model_id = "openai/gpt-oss-20b"
+output_dir = "$HOME/models/gpt-oss-20b-bf16"
+
+quantization_config = Mxfp4Config(dequantize=True)
+model_kwargs = dict(
+    attn_implementation="eager",
+    torch_dtype=torch.bfloat16,
+    quantization_config=quantization_config,
+    use_cache=False,
+    device_map="auto",
+)
+
+model = AutoModelForCausalLM.from_pretrained(model_id, **model_kwargs)
+
+# Patch config with custom attribute before saving
+model.config.attn_implementation = "eager"
+
+model.save_pretrained(output_dir)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+tokenizer.save_pretrained(output_dir)
+EOF
+
+python get_model.py
+
+
+
+model_dir=$HOME/models/gpt-oss-20b-bf16
+python3 -m verl.trainer.main_ppo \
+    algorithm.adv_estimator=grpo \
+    data.train_files="$gsm8k_train_path" \
+    data.val_files="$gsm8k_test_path" \
+    data.train_batch_size=1024 \
+    data.max_prompt_length=1024 \
+    data.max_response_length=1024 \
+    data.filter_overlong_prompts=True \
+    data.truncation='error' \
+    actor_rollout_ref.model.path=${model_dir} \
+    actor_rollout_ref.actor.optim.lr=1e-6 \
+    actor_rollout_ref.model.use_remove_padding=True \
+    actor_rollout_ref.actor.ppo_mini_batch_size=256 \
+    actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=32 \
+    actor_rollout_ref.actor.use_kl_loss=True \
+    actor_rollout_ref.actor.kl_loss_coef=0.001 \
+    actor_rollout_ref.actor.kl_loss_type=low_var_kl \
+    actor_rollout_ref.actor.entropy_coeff=0 \
+    actor_rollout_ref.model.enable_gradient_checkpointing=True \
+    actor_rollout_ref.actor.fsdp_config.param_offload=False \
+    actor_rollout_ref.actor.fsdp_config.optimizer_offload=False \
+    +actor_rollout_ref.actor.fsdp_config.model_dtype=bfloat16 \
+    actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=32 \
+    actor_rollout_ref.rollout.tensor_model_parallel_size=2 \
+    actor_rollout_ref.rollout.name=sglang \
+    actor_rollout_ref.rollout.engine_kwargs.sglang.attention_backend=triton \
+    actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
+    actor_rollout_ref.rollout.n=5 \
+    actor_rollout_ref.rollout.load_format=safetensors \
+    actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=32 \
+    actor_rollout_ref.ref.fsdp_config.param_offload=True \
+    algorithm.use_kl_in_reward=False \
+    trainer.critic_warmup=0 \
+    trainer.logger='["console","wandb"]' \
+    trainer.project_name='verl_grpo_example_gsm8k_math' \
+    trainer.experiment_name='oai_oss_20b_function_rm' \
+    trainer.n_gpus_per_node=8 \
+    trainer.nnodes=1 \
+    trainer.save_freq=50 \
+    trainer.test_freq=10 \
+    trainer.total_epochs=15 $@