Configuration Parsing Warning:In adapter_config.json: "peft.task_type" must be a string

Crate β€” CLAP LoRA for producer vocabulary

LoRA adapter over laion/clap-htsat-unfused fine-tuned so producer terms base CLAP barely knows β€” boom-bap, tape-saturated, rimshot, reese bass β€” pull the right audio. Part of Crate, sound-native search for music producers (hum / drop a track / describe it β†’ one embedding space).

Results β€” producer-vocab retrieval (held-out)

metric base CLAP fine-tuned
recall@1 0.210 0.405
recall@10 0.746 0.951
recall@5 0.580 0.868

Usage

from transformers import ClapModel, ClapProcessor
from peft import PeftModel

base = "laion/clap-htsat-unfused"
model = PeftModel.from_pretrained(ClapModel.from_pretrained(base), "jahnaviym/crate-clap-lora").merge_and_unload()
proc = ClapProcessor.from_pretrained(base)
# proc(text=[...]) / proc(audios=[...], sampling_rate=48000) β†’ get_text/audio_features

Training

  • Symmetric InfoNCE on (audio, text) pairs from Freesound (CC0/CC-BY) + free packs.
  • LoRA on the audio/text projection heads (r=16, alpha=32).
  • Label-preserving augmentation (pitch/stretch/noise/EQ) for positive pairs.

See the repo for the full pipeline and eval.

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