Instructions to use LabradorTransformer/Labrador with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use LabradorTransformer/Labrador with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("LabradorTransformer/Labrador") - Notebooks
- Google Colab
- Kaggle
File size: 559 Bytes
9cb83b9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"architectures": [
"BertForMaskedLM"
],
"attention_probs_dropout_prob": 0.1,
"classifier_dropout": null,
"hidden_act": "relu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 1024,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 90,
"model_type": "bert",
"num_attention_heads": 4,
"num_hidden_layers": 10,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"transformers_version": "4.24.0",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 4251
}
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