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.ckpt) serialise depuis le modele HuggingFace fine-tune
openai/whisper-small. Noms de tenseurs = state_dict HuggingFace,
type Float32 (relisible par mindspore.load_checkpoint).1import os; os.environ["HF_ENDPOINT"] = "https://huggingface.co"
2import mindspore as ms, torch # torch == mindtorch sous mindnlp
3from mindnlp.transformers import WhisperForConditionalGeneration, WhisperConfig
4
5cfg = WhisperConfig.from_pretrained("healthforallofus/are-bambara-asr-mindspore")
6model = WhisperForConditionalGeneration(cfg)
7pd = ms.load_checkpoint("are-bambara-asr.ckpt")
8model.load_state_dict({k: torch.from_numpy(v.asnumpy()) for k, v in pd.items()}, strict=False)
9model.eval()