Instructions to use hf-internal-testing/tiny-random-MegatronBertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MegatronBertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MegatronBertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MegatronBertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MegatronBertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c637a14a4d65a945b84901fdd30624a8c5e45a7e3c0a4632aadf452247c8ad50
- Size of remote file:
- 906 kB
- SHA256:
- 38e9070313ff95e43c9d5ccf176c00c70c46c22bbc59b9f04799bfd6c2f244d1
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