Upload ms-swift/examples/sampler/mcts/mcts.sh with huggingface_hub

ms-swift/examples/sampler/mcts/mcts.sh

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+export CUDA_VISIBLE_DEVICES=0
+export USE_OPENCOMPASS_EVALUATOR=True
+
+swift sample \
+    --model ./output/Qwen2.5-Math-7B-Instruct/v40-20250126-161112/checkpoint-20 \
+    --orm_model math \
+    --sampler_type mcts \
+    --sampler_engine vllm \
+    --output_dir ./output/sampler/mcts \
+    --system ./examples/sampler/system_prompt.txt \
+    --stop_words ки \
+    --dataset ./datasets/competition_math/small_test.jsonl \
+    --num_return_sequences 2 \
+    --process_reward_rate 0 \
+    --max_new_tokens 2048
+
+## Train
+# nproc_per_node=8
+# NPROC_PER_NODE=$nproc_per_node \
+# swift sft \
+#     --model Qwen/Qwen2.5-Math-7B-Instruct \
+#     --train_type full \
+#     --torch_dtype bfloat16 \
+#     --dataset 'datasets/gen_V5.jsonl' \
+#     --num_train_epochs 1 \
+#     --per_device_train_batch_size 1 \
+#     --learning_rate 1e-5 \
+#     --gradient_accumulation_steps $(expr 128 / $nproc_per_node) \
+#     --eval_steps 1000 \
+#     --save_steps 10 \
+#     --save_total_limit 100 \
+#     --max_length 10000 \
+#     --logging_steps 5 \
+#     --gradient_checkpointing_kwargs '{"use_reentrant": false}' \
+#     --deepspeed zero3