Instructions to use vtlustos/whisper-large-v2_lora_int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vtlustos/whisper-large-v2_lora_int8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vtlustos/whisper-large-v2_lora_int8")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vtlustos/whisper-large-v2_lora_int8") model = AutoModelForSpeechSeq2Seq.from_pretrained("vtlustos/whisper-large-v2_lora_int8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d7e54d1f6ab3534b5bc6ce11f8c952b951d267c2004e138a88eb80d4758a0ad
- Size of remote file:
- 3.84 kB
- SHA256:
- 5df841b1d0dafdf6d35d242344aa15438b154a92211b33e42b49992420c2a9f6
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