Instructions to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="trl-internal-testing/tiny-VoxtralForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc8853c1a9b547a0a82837cd3f176d4f23438fdb8d6182427125a08ff76a5220
- Size of remote file:
- 8.53 MB
- SHA256:
- 85376e912d8c74b0ff031dc5abc2f05d0faaef8f7c247baa828321f6b7a4aa73
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