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yehoshua01
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Model Details
Model Provider
yehoshua01
Model Tree
openai/whisper-large-v3-turbo
Input Modalities
Output Modalities
Supported Functionality
Witness (voter), and the one the shipped chain actually reads. Decode it under the placeholder language token <|sw|>, which is what it trained under: a language token is a learned decoder state, and <|ln|> selects one this checkpoint never saw.
Beam 3 gains +0.003369 over greedy on this checkpoint. As a solo Lingala half it scores 0.752910, i.e. -0.009491 against the shipped chain.
python
from transformers import WhisperForConditionalGeneration, WhisperProcessorimport torch, soundfile as sf, torchaudio.functional as AF proc = WhisperProcessor.from_pretrained("yehoshua01/waxal-whisper-turbo-lin-r1")model = WhisperForConditionalGeneration.from_pretrained("yehoshua01/waxal-whisper-turbo-lin-r1").eval().cuda()tok = proc.tokenizer# the language slot is a LEARNED decoder state -- use the token this checkpoint trained underforced = [(1, tok.convert_tokens_to_ids("<|sw|>")), (2, tok.convert_tokens_to_ids("<|transcribe|>")), (3, tok.convert_tokens_to_ids("<|notimestamps|>"))] wav, sr = sf.read("clip.wav", dtype="float32")wav = AF.resample(torch.from_numpy(wav), sr, 16_000).numpy()[:30 * 16_000]f = proc.feature_extractor(wav, sampling_rate=16_000, return_tensors="pt").input_featuresout = model.generate(f.to("cuda", model.dtype), forced_decoder_ids=forced, max_new_tokens=220)print(proc.batch_decode(out, skip_special_tokens=True)[0])| code, method, verification | yehoshua0/waxal-asr-phase2 |
| cached decodes and chain inputs | yehoshua01/waxal-phase2-chain-inputs |
| all checkpoints | yehoshua01 on the Hub |
Sibling checkpoints (primaries, voters and ablations of the same system): waxal-mms-1b-lin-pl2-spk · waxal-sunbird51-sna-pl2-spk · waxal-whisper-turbo-lin-r2 · waxal-qlora-largev3-lin · waxal-omni-ctc1b-lin · waxal-omni-ctc1b-sna · · · · ·
apache-2.0. Training data is google/WaxalNLP
(CC-BY-SA-4.0, share-alike), so derivatives carry that too.
These weights are not a general-purpose ASR model. Pseudo-labels were computed on the phase-2 test audio (transductive self-training, permitted for phase-2 training by the host), so the checkpoint is partly adapted to that specific set.
waxal-sunbird51-lin-ft-r2