Replication of the first 100 steps of AI2's OLMo-3 32B Think-SFT recipe (olmo-core,
AI2's pre-tokenized Dolci data, faithful data order). HF-format checkpoints at SFT
steps 0, 25, 50, 75, 100, one per subfolder (step0/ … step100/).
1from transformers import AutoModelForCausalLM, AutoTokenizer
2m = AutoModelForCausalLM.from_pretrained("cbai-eval-awareness/olmo3-32b-sft", subfolder="step50")
Used to trace verbalized eval-awareness (VEA) across early SFT.