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zondaxyz/babyconceptLM-English-matched
babyconceptLM-English-matched is a text generation model from zondaxyz. Use it when you need the model to write or continue text.
This repository contains the frozen English BabyConceptLM checkpoint used as the concept-side reference in the paper's matched-control comparison with zondaxyz/babyconceptLM-TA1-token-only-en.
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From the Hugging Face model README
This repository contains the frozen English BabyConceptLM checkpoint used as the concept-side reference in the paper's matched-control comparison with zondaxyz/babyconceptLM-TA1-token-only-en.
This is the archived e3_583_eng100m_full_dwa_A_stable experiment, not the distinct public-final BabyLM submission in zondaxyz/babyconceptLM-583-en.
e3_583_eng100m_full_dwa_A_stablepytorch_model.bin SHA-256: 55ba4c4cb71dfa102ce283ee67f8ab5d9cd6abb7eeb5e038a38266dff6836ba8The repository includes the tokenizer, configuration, model weights, and custom Transformers-compatible loading code. The optimizer/training state is intentionally omitted because it is not required for inference or frozen evaluation. Machine-specific absolute paths from the original training summary are also omitted; a portable recipe summary is provided in matched_provenance.json.
from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "zondaxyz/babyconceptLM-English-matched"
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(repo_id, trust_remote_code=True)
The model uses repository-provided custom code, so inspect the pinned revision before enabling trust_remote_code=True in security-sensitive environments.
The checkpoint is released for reproducibility of the frozen English matched-control analyses. It should not be substituted for zondaxyz/babyconceptLM-583-en: the two repositories contain different trained weights and use different frozen recipes.