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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from trl-internal-testing/tiny-VoxtralForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 191 Bytes
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https://huggingface.co/trl-internal-testing/tiny-VoxtralForConditionalGeneration/resolve/refs%2Fpr%2F1/README.md
- Command line
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hf download hf://trl-internal-testing/tiny-VoxtralForConditionalGeneration@refs/pr/1/README.md
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curl -L -o README.md https://huggingface.co/trl-internal-testing/tiny-VoxtralForConditionalGeneration/resolve/refs%2Fpr%2F1/README.md
191 Bytes
| library_name: transformers | |
| tags: | |
| - trl | |
| # Tiny VoxtralForConditionalGeneration | |
| This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library. | |