GLM-5.2 is live. #1 throughput on OpenRouter, pay-per-token on FriendliAI. Try it today ➜
epfl-dlab
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Run this model inference with full control and performance in your environment.
Model Details
Model Provider
epfl-dlab
Model Tree
Input Modalities
Output Modalities
Supported Functionality
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.
<assistant> marker and constitution tokens (vocabulary 49280).Intermediate checkpoints are published as git revisions on this repo, so any point in the trajectory can be loaded by passing revision=:
python
from transformers import AutoModelForCausalLM, AutoTokenizerimport torchrepo = "epfl-dlab/spp-t0-3b-base"tok = AutoTokenizer.from_pretrained(repo) # identical at every revisionmodel = 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 |
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.
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.
License: to be finalised.
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 |