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while-ai/course-refunds-sft-1.5b
course-refunds-sft-1.5b is a text generation model from while-ai. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as apache-2.0.
Recipe: recipes/04-train/sft · Collection: Course and community runs
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From the Hugging Face model README
Recipe: recipes/04-train/sft · Collection: Course and community runs
Lesson 7 of the course: SFT on the course's own 46-row export, on one A10G, in six minutes. Base pass@1 0.25 to 0.73 on 40 held-out tasks the training never saw.
| pass@1 | 95% CI | pass^4 | pass@4 | |
|---|---|---|---|---|
| before (base, seed 1) | 0.25 | [0.16, 0.35] | 0.07 | 0.48 |
| after (this adapter) | 0.73 | [0.63, 0.81] | 0.41 | 0.95 |
Paired delta +0.481 [+0.342, +0.616] over 40 tasks. Three base passes gave run_std 0.002, so a delta under 0.011 is noise. Loss 3.07 to 0.80 over 40 steps, 35 seconds of training. The full log is in the recipe README under What you get.
The root holds the arm the recipe README's headline number reports. Every other arm is a subfolder named after it. checkpoints/ never ships.
| folder | arm |
|---|---|
. | SFT, 40 steps, run lesson7-sft |
from peft import PeftModel
from transformers import AutoModelForCausalLM
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")
model = PeftModel.from_pretrained(base, "while-ai/course-refunds-sft-1.5b") # the headline arm
git clone https://github.com/whilehq/whileai-sdk && cd whileai-sdk/recipes/04-train/sft
modal run train_modal.py --data train.jsonl
The recipe README pins the seed, the library versions and the GPU, and its Checks table says what the eval verified. Read the Learned section before quoting a number from this card.