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run_20260803_gemma3_4b_full_sdf_framing_seed42/| Checkpoint | Path |
|---|---|
| Refreshed control | refreshed_control/ |
| America immediately after SDF | post_sdf_pro_america/ |
| America after instruction refresher | refreshed_pro_america/ |
| Affordability immediately after SDF | post_sdf_pro_affordability/ |
| Affordability after instruction refresher | refreshed_pro_affordability/ |
families/ contains all 22 rank-64 cheese-AFT adapters, standard evaluations,
prompt-swap evaluations, logs, manifests, and completion records. data/
contains the exact staged SDF, instruction-refresher, cheese train, and held-out
files used by the run.google/gemma-3-4b-it@093f9f388b31de276ce2de164bdc2081324b9767.
The experiment is text-only: the checkpoints contain the exact
Gemma3ForCausalLM language backbone and LM head, without the unused vision
tower or multimodal projector.1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3repo = "sidbaines/gemma3-4b-cheese-full-sdf"
4prefix = "run_20260803_gemma3_4b_full_sdf_framing_seed42"
5model = AutoModelForCausalLM.from_pretrained(
6 repo,
7 subfolder=f"{prefix}/refreshed_pro_america",
8 torch_dtype="auto",
9)
10tokenizer = AutoTokenizer.from_pretrained(
11 repo,
12 subfolder=f"{prefix}/refreshed_pro_america",
13)families/pro_america_sdf/ip_pro_america/adapter/ and should be applied to the
matching refreshed substrate.luke-sid-baines-blank/gemma3-4b-cheese-full-sdf.