Instructions to use hf-internal-testing/tiny-random-ProphetNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ProphetNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-ProphetNetModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ProphetNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ProphetNetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9d3fcf4d828370b9a647ccd17ee027b36f2099243a73083b5314aecdad20b72
- Size of remote file:
- 2.14 MB
- SHA256:
- 63c7e856a7c7c36d8efe00fb48b0e8b9193b8b07848f47f7b53d2975a1cca677
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