Instructions to use Edcastro/edcastr_ASR_WhisperSmall_LatinSpanishAllLocale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Edcastro/edcastr_ASR_WhisperSmall_LatinSpanishAllLocale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Edcastro/edcastr_ASR_WhisperSmall_LatinSpanishAllLocale")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Edcastro/edcastr_ASR_WhisperSmall_LatinSpanishAllLocale") model = AutoModelForSpeechSeq2Seq.from_pretrained("Edcastro/edcastr_ASR_WhisperSmall_LatinSpanishAllLocale", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2cfcec9370196037f4fefa48846fe9606cb1bff96f3943bf1d54c97acf3827e
- Size of remote file:
- 5.62 kB
- SHA256:
- ebe75cde8d3de3e966822c702e81b73cb0f821fc567fd005fb4fa6441c8bcbe9
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