epfl-dlab / spp-t0-3b-base

huggingface.co
Total runs: 13
24-hour runs: 0
7-day runs: -18
30-day runs: -99
Model's Last Updated: July 30 2026
text-generation

Introduction of spp-t0-3b-base

Model Details of spp-t0-3b-base

SPP-T0 — Base (3B)

Type: base (pretrained) model. Not instruction-tuned and ships no chat template.

Trained with Synthetic Persona Pretraining (SPP) from token zero: first-person reflections are inserted into the roughly 10% of annotated documents that carry one, throughout the entire pretraining run.

Synthetic Persona Pretraining (SPP)

Synthetic Persona Pretraining (SPP) installs a target value persona during pretraining rather than only during alignment. Value-laden, first-person reflections, generated against a constitution, are appended to a subset of pretraining documents after a special <assistant> token. Attention masking and RoPE position aliasing keep the reflection from changing the continuation of the original document. This model is trained with SPP.

Instruction-tuned counterpart: epfl-dlab/spp-t0-3b-instruct .

Model details
  • Architecture: Llama-3.2-3B-shaped, trained from scratch.
  • Tokenizer: the SmolLM2 tokenizer extended with an <assistant> marker and constitution tokens (vocabulary 49280).
  • Pretraining: ~500B tokens on a subset of the Olmo 3 Dolma 3 mixture, with SPP reflections inserted into the safety-annotated documents within it.
Training checkpoints

Intermediate checkpoints are published as git revisions on this repo, so any point in the trajectory can be loaded by passing revision= :

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "epfl-dlab/spp-t0-3b-base"
tok = AutoTokenizer.from_pretrained(repo)          # identical at every revision
model = AutoModelForCausalLM.from_pretrained(
    repo, revision="step-25000", dtype=torch.bfloat16, device_map="auto"
)
Revision Pretraining step Tokens seen LR phase
step-25000 25,000 / 254,313 ~49.2B stable
step-50000 50,000 / 254,313 ~98.3B stable
step-75000 75,000 / 254,313 ~147B stable
step-100000 100,000 / 254,313 ~197B stable
step-125000 125,000 / 254,313 ~246B stable
step-150000 150,000 / 254,313 ~295B stable
step-175000 175,000 / 254,313 ~344B stable
step-200000 200,000 / 254,313 ~393B stable
step-225000 225,000 / 254,313 ~442B stable
step-240000 240,000 / 254,313 ~472B linear decay
step-254313 254,313 / 254,313 ~500B linear decay — same weights as main

main always holds the finished model (step 254,313). Only model weights are published — optimizer and RNG state are not included, so these revisions support evaluation, probing, and fine-tuning, but not exact resumption of the original run.

Intended use

Research on alignment and safety. As a base model it is meant for continuation, probing, or further fine-tuning; it is not instruction-tuned and can produce incorrect or unsafe content.

Links

License: to be finalised.

Runs of epfl-dlab spp-t0-3b-base on huggingface.co

13
Total runs
0
24-hour runs
-2
3-day runs
-18
7-day runs
-99
30-day runs

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Updated:January 15 2025