Instructions to use hf-tiny-model-private/tiny-random-MegatronBertModel 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-MegatronBertModel 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-MegatronBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1ba1f597154f4ca6fe6449b249290b336050b465aa717383f420a658bc62403
- Size of remote file:
- 888 kB
- SHA256:
- 6653eeca56cc41d1890e80f397188e757ad91d795c891dc41987cad8ef38e67f
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