{ "mic": "0.3", "name": "MusicGen Melody text- and melody-conditioned music generation", "usage": "AutoProcessor + MusicgenMelodyForConditionalGeneration.generate, text and melody prompts, classifier-free guidance, batched", "architecture": "MusicgenMelodyForConditionalGeneration", "checkpoints": { "facebook/musicgen-melody": { "fixture": "hf-internal-testing/mic-musicgen-melody-slim" } }, "fixtures": { "hf-internal-testing/mic-musicgen-melody-slim": { "built_from": "facebook/musicgen-melody", "covers": [ "facebook/musicgen-melody" ], "build": { "seed": 17, "config_overrides": { "fields": { "audio_encoder.num_filters": 4, "audio_encoder.codebook_dim": 64 }, "reason": "The generic rule shrinks EnCodec's hidden_size but not num_filters, which doubles at each of its four stages (64 filters reach 1024 channels at the LSTM, 56M of 59M parameters), nor codebook_dim, which must equal hidden_size for the decoder to accept the quantizer's output." }, "overfit": "Random weights pass the input-sensitivity gate (teacher-forced logits move), but greedy generation ignores the conditioning: both prompts, with or without a melody, give the same audio codes, so a change that drops the text or melody conditioning would go unseen." } } }, "integrations": { "transformers": { "entry_point": "integrations/transformers/usage.md", "format": "runnable-markdown", "requires": [ "transformers>=5", "torch", "sentencepiece" ], "targets": [ "fixtures", "checkpoints" ], "variants": { "default": {}, "eager": { "attn_implementation": "eager" }, "bfloat16": { "dtype": "bfloat16" } }, "training": true, "resources": { "fixture": { "memory_gb": 1, "download_mb": 20 }, "facebook/musicgen-melody": { "memory_gb": 12, "download_mb": 6230 } } } }, "outputs": { "runtime": { "compare": "exact" }, "input_feature_shape": { "compare": "exact" }, "codes": { "compare": "exact" }, "audio_shape": { "compare": "exact" }, "audio_head": { "compare": "allclose", "atol": 0.0001, "rtol": 0.0001 }, "text_only_codes": { "compare": "exact" }, "training.loss": { "compare": "allclose", "atol": 0.0001, "rtol": 0.0001 }, "training.gradients": { "compare": "all_true" }, "training.updated": { "compare": "true" } } }