facebook/bart-base

huggingface-mic/bart-base-mic@1d300e47ad35 ← facebook/bart-base@aadd2ab0ae0c · BartForConditionalGeneration · overfit weights · built before the shrink rule (no recorded recipe)

Original139.4Mparameters

Fixture3.5Mparameters

Layer stacks2compared

Findings0to review

✓ Same architecture, smaller

Every module class, layer kind and checked property of the original is in the fixture.

One square per layer, colored by kind: the layer's module classes and type attributes. Hover a square for its index and kind.

Original · 6

Fixture · 2

Kind	Original	Fixture
EncoderLayer	6	2	✓ kept

Original · 6

Fixture · 2

Kind	Original	Fixture
DecoderLayer	6	2	✓ kept

Share of each model's parameters per component. Vocabulary and patch sizes are kept, so embeddings usually take a larger share of the fixture.

Original

Fixture

Component	Original	Share	Fixture	Share
model.decoder.layers	56.7M	40.7%	100.5K	2.9%
model.encoder.layers	42.5M	30.5%	66.9K	1.9%
model.shared	38.6M	27.7%	3.2M	91.5%
model.encoder	789.5K	0.6%	65.8K	1.9%
model.decoder	789.5K	0.6%	65.8K	1.9%

Config	Property	Original	Fixture
model	model_type	bart	bart	✓ kept
model	vocab_size	50265	50265	✓ kept
model	tie_word_embeddings	True	True	✓ kept
model	max_position_embeddings	1024	1024	✓ kept

Instances of each class in the built model (prefix Bart omitted).

Class	Original	Fixture
Linear	97	33
LayerNorm	32	12
Attention	18	6
GELUActivation	12	4
DecoderLayer	6	2
EncoderLayer	6	2
ScaledWordEmbedding	3	3
LearnedPositionalEmbedding	2	2
ModuleList	2	2
Decoder	1	1
Encoder	1	1
ForConditionalGeneration	1	1
Model	1	1

7 fields changed, 35 unchanged.