Automatic Speech Recognition
Transformers
Safetensors
PyTorch
mini_whisper
text2text-generation
custom_code
Instructions to use NeuraCraft/MiniWhisper-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuraCraft/MiniWhisper-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NeuraCraft/MiniWhisper-ASR", trust_remote_code=True)# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("NeuraCraft/MiniWhisper-ASR", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| # mini_whisper_model.py - Backwards compatibility alias | |
| from configuration_mini_whisper import MiniWhisperConfig | |
| from modeling_mini_whisper import ( | |
| MiniWhisperForConditionalGeneration, | |
| MiniWhisperModel, | |
| MiniWhisperEncoder, | |
| MiniWhisperDecoder, | |
| ) | |
| from transformers import CONFIG_MAPPING, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING | |
| CONFIG_MAPPING.register("mini_whisper", MiniWhisperConfig) | |
| try: | |
| MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING.register(MiniWhisperConfig, MiniWhisperForConditionalGeneration) | |
| except Exception: | |
| pass | |
| MiniWhisperConfig.register_for_auto_class("AutoConfig") | |
| MiniWhisperForConditionalGeneration.register_for_auto_class("AutoModelForSeq2SeqLM") | |
| __all__ = [ | |
| "MiniWhisperConfig", | |
| "MiniWhisperForConditionalGeneration", | |
| "MiniWhisperModel", | |
| "MiniWhisperEncoder", | |
| "MiniWhisperDecoder", | |
| ] |