Instructions to use meric533/socrateach-sft-olmo2-1b-lora-run2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use meric533/socrateach-sft-olmo2-1b-lora-run2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-0425-1B-Instruct") model = PeftModel.from_pretrained(base_model, "meric533/socrateach-sft-olmo2-1b-lora-run2") - Notebooks
- Google Colab
- Kaggle
Fix math numbers (0.468/0.208 vs 0.456/0.212)
Browse files
README.md
CHANGED
|
@@ -21,10 +21,12 @@ measure the pedagogy judge's noise floor against training noise.
|
|
| 21 |
|---|---|---|
|
| 22 |
| repo | [`socrateach-sft-olmo2-1b-lora`](https://huggingface.co/meric533/socrateach-sft-olmo2-1b-lora) | `socrateach-sft-olmo2-1b-lora-run2` |
|
| 23 |
| judge OVERALL (no SI, deduped) | 0.685 | 0.527 |
|
| 24 |
-
| GSM8K
|
|
|
|
| 25 |
|
| 26 |
-
Same
|
| 27 |
-
|
|
|
|
| 28 |
|
| 29 |
## Why this pair matters
|
| 30 |
|
|
|
|
| 21 |
|---|---|---|
|
| 22 |
| repo | [`socrateach-sft-olmo2-1b-lora`](https://huggingface.co/meric533/socrateach-sft-olmo2-1b-lora) | `socrateach-sft-olmo2-1b-lora-run2` |
|
| 23 |
| judge OVERALL (no SI, deduped) | 0.685 | 0.527 |
|
| 24 |
+
| GSM8K bare | 0.468 | 0.456 |
|
| 25 |
+
| GSM8K hinted | 0.208 | 0.212 |
|
| 26 |
|
| 27 |
+
Same recipe, independently trained (run 1 comes from the earlier POC). They are genuinely
|
| 28 |
+
different weights, not a re-upload of one checkpoint. Note how tightly the *math* numbers
|
| 29 |
+
agree — 0.012 and 0.004 apart — compared to the judge gap below.
|
| 30 |
|
| 31 |
## Why this pair matters
|
| 32 |
|