Remote code revision 2: generate() honours max_length / stopping_criteria / logits_processor and the other standard transformers arguments (revision 1 always produced 128 new tokens, truncating CoT under lm-eval); tie_weights() is a no-op at the top level; card documents the change. Weights unchanged.
9ef97cf verified | from transformers import PretrainedConfig | |
| class MatildaPlatypusConfig(PretrainedConfig): | |
| """A Matilda Platypus model: the lower block of a larger Qwen3 parent, a learned linear Representation Bridge, | |
| and the upper block (plus final norm and output head) of a smaller Qwen3 parent.""" | |
| model_type = "matilda-platypus" | |
| def __init__(self, lower_model="Qwen/Qwen3-8B-Base", lower_layers=25, upper_model="upper_block", | |
| upper_start_layer=25, upper_layers=11, bridge_file="bridge.safetensors", | |
| lower_hidden_size=4096, upper_hidden_size=2560, vocab_size=151936, | |
| max_position_embeddings=None, **kwargs): | |
| self.lower_model = lower_model # hub id, or a sub-folder of this repo | |
| self.lower_layers = lower_layers # k: decoder layers kept from the larger parent (layers 1..k) | |
| self.upper_model = upper_model # sub-folder holding the adapted smaller parent (HF checkpoint) | |
| self.upper_start_layer = upper_start_layer # 0-based index of the first retained upper layer (= j - 1) | |
| self.upper_layers = upper_layers # m: decoder layers kept from the smaller parent | |
| self.bridge_file = bridge_file | |
| self.lower_hidden_size = lower_hidden_size | |
| self.upper_hidden_size = upper_hidden_size | |
| self.vocab_size = vocab_size | |
| # context length; filled in from the parents at load time when not given (harnesses read it) | |
| self.max_position_embeddings = max_position_embeddings | |
| # The lower block's embedding (d_lower) and the upper block's output head (d_upper) differ in width and are | |
| # never tied; PretrainedConfig would otherwise default this to True and generic tie_weights() calls would | |
| # try to tie them. | |
| kwargs.setdefault("tie_word_embeddings", False) | |
| super().__init__(**kwargs) | |