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
Upload config.json with huggingface_hub
Browse files- config.json +2 -2
config.json
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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "/tmp/
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"architectures": [
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"BertModel"
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],
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"position_embedding_type": "absolute",
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"task": "text-classification",
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"torchscript": true,
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"transformers_version": "4.
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"type_vocab_size": 16,
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"use_cache": true,
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"vocab_size": 1124
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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "/tmp/tmpdl6f42qj",
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"architectures": [
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"BertModel"
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],
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"position_embedding_type": "absolute",
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"task": "text-classification",
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"torchscript": true,
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"transformers_version": "4.46.2",
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"type_vocab_size": 16,
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"use_cache": true,
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"vocab_size": 1124
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