{
  "attention_probs_dropout_prob": 0.1,
  "hidden_dropout_prob": 0.1,
  "hidden_size": 384,
  "intermediate_size": 1280,
  "max_position_embeddings": 512,
  "position_bucket_size": 32,
  "num_attention_heads": 6,
  "num_hidden_layers": 12,
  "vocab_size": 8192,
  "layer_norm_eps": 1e-05
}

Tokenizer file: tokenizer_nso_vs8192.json

Quick Usage

python

from transformers import AutoTokenizer, AutoModelForMaskedLM
model_id = 'haznitrama/babybabellm-gpt_bert-nso-main'
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForMaskedLM.from_pretrained(model_id, trust_remote_code=True)
out = model(**tok('Hello world', return_tensors='pt'))

Notes

Converted on 2025-09-28T11:11:41.835362+00:00
Weights are the exact trained parameters; no new layers were initialized.
Requires trust_remote_code=True due to custom architecture.