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gizemyc/pythia-160m-c4-dyck-ppt
pythia-160m-c4-dyck-ppt is a machine learning model from gizemyc. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Pythia-160M pre-pretrained on k-shuffle Dyck, then pretrained on C4.
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From the Hugging Face model README
Pythia-160M pre-pretrained on k-shuffle Dyck, then pretrained on C4.
Part of an experiment reproducing and extending the pruning analysis from "Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases" (Hu et al., 2025, arXiv:2502.19249).
The hypothesis under test: pre-pretraining on English itself yields attention-head circuits as sparse/transferable as pre-pretraining on k-shuffle Dyck.
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("gizemyc/pythia-160m-c4-dyck-ppt")
tokenizer = AutoTokenizer.from_pretrained("gizemyc/pythia-160m-c4-dyck-ppt")
EleutherAI/pythia-160m (12 layers x 12 heads)