初始化项目，由ModelHub XC社区提供模型

Model: AliceYin/l20-edu-135m
Source: Original Platform

training_artifacts/scripts/eval_smollm_benchmark.sh

@@ -0,0 +1,71 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+TASKS="${TASKS:-arc_challenge,arc_easy,hellaswag,lambada_openai,piqa,winogrande}"
+DEVICE="${DEVICE:-cuda:0}"
+DTYPE="${DTYPE:-bfloat16}"
+BATCH_SIZE="${BATCH_SIZE:-auto}"
+OUTPUT_ROOT="${OUTPUT_ROOT:-eval_results/smollm_target_$(date +%Y%m%d_%H%M%S)}"
+REQUESTED_CANDIDATE="${CANDIDATE:-}"
+
+export HF_ENDPOINT="${HF_ENDPOINT:-https://hf-mirror.com}"
+export HF_HUB_DISABLE_XET="${HF_HUB_DISABLE_XET:-1}"
+
+if ! command -v lm_eval >/dev/null 2>&1; then
+  echo "lm_eval is not on PATH. Activate the eval environment first, for example: source .venv-eval/bin/activate" >&2
+  exit 2
+fi
+
+sanitize_name() {
+  echo "$1" | tr '/: ' '___'
+}
+
+declare -a MODELS
+if [ "$#" -gt 0 ]; then
+  MODELS=("$@")
+  CANDIDATE="${REQUESTED_CANDIDATE:-${1%%=*}}"
+else
+  MODELS=(
+    "ours-stage2=runs/l20-edu-135m-stage2-math-code-textbook-replay-8k/step-001850"
+    "smollm-135m=HuggingFaceTB/SmolLM-135M"
+    "smollm2-135m=HuggingFaceTB/SmolLM2-135M"
+  )
+  if [ -e "runs/l20-edu-135m-stage2-replay-polish-8k/final" ] || [ -e "runs/l20-edu-135m-stage2-replay-polish-8k/step-000300" ]; then
+    MODELS=("ours-polish=runs/l20-edu-135m-stage2-replay-polish-8k/final" "${MODELS[@]}")
+    CANDIDATE="${REQUESTED_CANDIDATE:-ours-polish}"
+  else
+    CANDIDATE="${REQUESTED_CANDIDATE:-ours-stage2}"
+  fi
+fi
+
+mkdir -p "$OUTPUT_ROOT"
+declare -a RESULTS
+
+for entry in "${MODELS[@]}"; do
+  if [[ "$entry" != *=* ]]; then
+    echo "Expected model entry NAME=MODEL_PATH_OR_HF_ID, got: $entry" >&2
+    exit 2
+  fi
+  name="${entry%%=*}"
+  model="${entry#*=}"
+  out_dir="$OUTPUT_ROOT/$(sanitize_name "$name")"
+  echo "==> Evaluating $name: $model"
+  lm_eval \
+    --model hf \
+    --model_args "pretrained=${model},dtype=${DTYPE}" \
+    --tasks "$TASKS" \
+    --device "$DEVICE" \
+    --batch_size "$BATCH_SIZE" \
+    --output_path "$out_dir" \
+    --log_samples
+  RESULTS+=("--result" "${name}=${out_dir}")
+done
+
+python scripts/summarize_smollm_benchmark.py \
+  "${RESULTS[@]}" \
+  --candidate "$CANDIDATE" \
+  --baseline smollm-135m \
+  --baseline smollm2-135m \
+  --out-md "$OUTPUT_ROOT/summary.md" \
+  --out-json "$OUTPUT_ROOT/summary.json" \
+  --out-csv "$OUTPUT_ROOT/summary.csv"