Instructions to use optimum-internal-testing/tiny_random_bert_neuronx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-internal-testing/tiny_random_bert_neuronx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="optimum-internal-testing/tiny_random_bert_neuronx")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("optimum-internal-testing/tiny_random_bert_neuronx") model = AutoModel.from_pretrained("optimum-internal-testing/tiny_random_bert_neuronx") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1572b0c46d98715fe5c5fc4726fe1d557613affc342a039771ee16524120f25a
- Size of remote file:
- 444 kB
- SHA256:
- ba3df62d6b19cb979a5326425292e133ed7ea6037ad5f738cd53df04174ea6a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.