Instructions to use onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/audio_encoder.onnx_data from onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 310 kB
-
https://huggingface.co/onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration/resolve/refs%2Fpr%2F2/onnx/audio_encoder.onnx_data
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration@refs/pr/2/onnx/audio_encoder.onnx_data
-
curl -L -o audio_encoder.onnx_data https://huggingface.co/onnx-internal-testing/tiny-random-GraniteSpeechForConditionalGeneration/resolve/refs%2Fpr%2F2/onnx/audio_encoder.onnx_data
310 kB
- Xet hash:
- 84b3187dc52c744464177268943976bf159492828ad4f438fc399342ff19908c
- Size of remote file:
- 310 kB
- SHA256:
- 4fc318c65adfab915efc756e1a8b414bb71f97b076dece9e05474ca12289af32
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