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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb82c26d0806f9b6e7aeb1fe8b88c147fc89eff51b89767aef2669253a1e2dba
- Size of remote file:
- 1.29 GB
- SHA256:
- 27f82f6bf8350a414a670833eedc4e327a8e47912044e0d345379b0f7889d2d0
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