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
File size: 235 Bytes
e63b833 | 1 2 3 4 5 6 7 8 9 10 11 | {
"_from_model_config": true,
"bos_token_id": 100257,
"eos_token_id": 100257,
"output_attentions": false,
"output_hidden_states": false,
"pad_token_id": 100256,
"transformers_version": "5.3.0.dev0",
"use_cache": true
}
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