facebook/nllb-200-distilled-600M

huggingface-mic/nllb-200-distilled-600M-mic@fcaaa8d89cb3 ← facebook/nllb-200-distilled-600M@f8d333a098d1 · M2M100ForConditionalGeneration · random weights · built before the shrink rule (no recorded recipe)

Original615.1Mparameters

Fixture16.6Mparameters

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 · 12

Fixture · 2

Kind	Original	Fixture
EncoderLayer	12	2	✓ kept

Original · 12

Fixture · 2

Kind	Original	Fixture
DecoderLayer	12	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.shared	262.4M	42.7%	16.4M	99.0%
model.decoder.layers	201.6M	32.8%	100.5K	0.6%
model.encoder.layers	151.2M	24.6%	66.9K	0.4%
model.encoder	2.0K	0.0%	128	0.0%
model.decoder	2.0K	0.0%	128	0.0%

Config	Property	Original	Fixture
model	model_type	m2m_100	m2m_100	✓ kept
model	vocab_size	256206	256206	✓ kept
model	tie_word_embeddings	True	True	✓ kept
model	max_position_embeddings	1024	1024	✓ kept

Instances of each class in the built model (prefix M2M100 omitted).

Class	Original	Fixture
Linear	193	33
LayerNorm	62	12
Attention	36	6
ReLU	24	4
DecoderLayer	12	2
EncoderLayer	12	2
ScaledWordEmbedding	3	3
SinusoidalPositionalEmbedding	2	2
ModuleList	2	2
Decoder	1	1
Encoder	1	1
ForConditionalGeneration	1	1
Model	1	1

7 fields changed, 26 unchanged.