Instructions to use hf-tiny-model-private/tiny-random-ProphetNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ProphetNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ProphetNetModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6136def4b546709bb48e27f15934a752b47ac7c18918bc61d3083380bf75199d
- Size of remote file:
- 2.14 MB
- SHA256:
- a698a93d2db6668d9a6a54c66e7f255e50fe0a368ea8732a004479fed60e3c66
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