chore: import upstream snapshot with attribution

examples/train/rlhf/ppo/full.sh

@@ -0,0 +1,37 @@
+# 8 * 65 GiB
+# Currently, it only supports the case where the model and reward_model use the same template/tokenizer.
+# Currently, multimodal model PPO is not supported.
+
+# pip install "deepspeed==0.14.*"
+nproc_per_node=8
+
+PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
+CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
+NPROC_PER_NODE=$nproc_per_node \
+swift rlhf \
+    --rlhf_type ppo \
+    --model LLM-Research/Meta-Llama-3.1-8B-Instruct \
+    --reward_model 'AI-ModelScope/Skywork-Reward-Llama-3.1-8B-v0.2' \
+    --tuner_type full \
+    --dataset 'AI-ModelScope/alpaca-gpt4-data-zh#20000' 'AI-ModelScope/alpaca-gpt4-data-en#20000' \
+    --load_from_cache_file true \
+    --split_dataset_ratio 0.01 \
+    --torch_dtype bfloat16 \
+    --num_train_epochs 1 \
+    --per_device_train_batch_size 1 \
+    --per_device_eval_batch_size 1 \
+    --learning_rate 1e-6 \
+    --gradient_accumulation_steps $(expr 16 / $nproc_per_node) \
+    --eval_steps 100 \
+    --save_steps 100 \
+    --save_total_limit 2 \
+    --logging_steps 5 \
+    --max_length 2048 \
+    --output_dir output \
+    --warmup_ratio 0.05 \
+    --dataloader_num_workers 4 \
+    --deepspeed zero3 \
+    --response_length 512 \
+    --temperature 0.7 \
+    --dataset_num_proc 4 \
+    --save_only_model true

examples/train/rlhf/ppo/lora.sh

@@ -0,0 +1,40 @@
+# 4 * 50GiB
+# Currently, it only supports the case where the model and reward_model use the same template/tokenizer.
+# Currently, multimodal model PPO is not supported.
+
+# pip install "deepspeed==0.14.*"
+nproc_per_node=4
+
+PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
+CUDA_VISIBLE_DEVICES=0,1,2,3 \
+NPROC_PER_NODE=$nproc_per_node \
+swift rlhf \
+    --rlhf_type ppo \
+    --model LLM-Research/Meta-Llama-3.1-8B-Instruct \
+    --reward_model 'AI-ModelScope/Skywork-Reward-Llama-3.1-8B-v0.2' \
+    --tuner_type lora \
+    --dataset 'AI-ModelScope/alpaca-gpt4-data-zh#20000' 'AI-ModelScope/alpaca-gpt4-data-en#20000' \
+    --load_from_cache_file true \
+    --split_dataset_ratio 0.01 \
+    --torch_dtype bfloat16 \
+    --num_train_epochs 1 \
+    --per_device_train_batch_size 1 \
+    --per_device_eval_batch_size 1 \
+    --learning_rate 1e-5 \
+    --lora_rank 8 \
+    --lora_alpha 32 \
+    --target_modules all-linear \
+    --gradient_accumulation_steps $(expr 16 / $nproc_per_node) \
+    --eval_steps 100 \
+    --save_steps 100 \
+    --save_total_limit 2 \
+    --logging_steps 5 \
+    --max_length 2048 \
+    --output_dir output \
+    --warmup_ratio 0.05 \
+    --dataloader_num_workers 4 \
+    --deepspeed zero2 \
+    --response_length 512 \
+    --temperature 0.7 \
+    --dataset_num_proc 4 \
+    --save_only_model true