Update README.md

README.md

@@ -23,11 +23,6 @@ Two model families:
 - **LittleLearner** — pretrained on the K–5-filtered corpus.
 - **Unfiltered** — pretrained on the same corpus without the K–5 filter (baseline general corpus).
 
-Post-training data uses the same two names:
-
-- **K-5** — the K–5-filtered instruction/SFT corpus (matched to LittleLearner pretraining).
-- **Unfiltered** — the unfiltered instruction/SFT corpus.
-
 ---
 
 ## Released checkpoints
@@ -49,19 +44,9 @@ Encoded as **(pretrain → post-training)**:
 | Pretrain → Post-training | Description | Repo |
 |---|---|---|
 | LittleLearner → K-5           | Matched-pipeline LL post-training | `littlelearner/littlelearner-5b-bounded-sft-chatty` |
-| LittleLearner → Unfiltered    | Hybrid: LL pretrain, Unfiltered post-training data | `<...>` |
 | Unfiltered → Unfiltered       | Matched-pipeline Unfiltered post-training | `littlelearner/littlelearner-5b-unbounded-sft-chatty` |
 
 
----
-
-## Which checkpoint should I use?
-
-- **Studying the effect of the K-5 filter on pretraining** → paired base checkpoints at matched sizes (`…-bounded` vs `…-unbounded`).
-- **K-5 math / educational assistant** → LittleLearner → K-5 SFT+GRPO chatty.
-- **General-purpose small assistant** → Unfiltered → Unfiltered SFT+GRPO chatty.
-- **Effect of post-training data on a filtered pretrain** → compare the two `LittleLearner → …` SFT+GRPO variants.
-
 ---
 
 ## Important inference notes