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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +3 -2
config.json
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{
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"_name_or_path": "/
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"architectures": [
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"BertModel"
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"logits"
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],
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"static_batch_size": 1,
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"static_sequence_length": 32
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},
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"num_attention_heads": 4,
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"num_hidden_layers": 5,
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{
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"_name_or_path": "/tmp/tmpqlt7mor6",
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"architectures": [
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"BertModel"
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],
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"logits"
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],
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"static_batch_size": 1,
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"static_sequence_length": 32,
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"tensor_parallel_size": 1
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},
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"num_attention_heads": 4,
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"num_hidden_layers": 5,
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