Port distilbert transformer checkpoint #1736
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mattdangerw
reviewed
Aug 5, 2024
| transformers_config = load_config(preset, HF_CONFIG_FILE) | ||
| keras_config = convert_backbone_config(transformers_config) | ||
| backbone = cls(**keras_config) | ||
| print(backbone.summary()) |
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| def load_distilbert_tokenizer(cls, preset): | ||
| return cls( | ||
| get_file(preset, "vocab.txt"), |
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should we handle do_lower_case like we do for bert?
| "vocabulary_size": transformers_config["vocab_size"], | ||
| "num_layers": transformers_config["n_layers"], | ||
| "num_heads": transformers_config["n_heads"], | ||
| "hidden_dim": transformers_config["hidden_dim"] // 4, |
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shouldn't this just be transformers_config["dim"]?
| "num_layers": transformers_config["n_layers"], | ||
| "num_heads": transformers_config["n_heads"], | ||
| "hidden_dim": transformers_config["hidden_dim"] // 4, | ||
| "intermediate_dim": transformers_config["dim"] * 4, |
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shouldn't this just be transformers_config["hidden_dim"]?
mattdangerw
approved these changes
Aug 6, 2024
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Hi @mattdangerw @ariG23498,
Ported distilbert transformers checkpoint in kerasNLP. Please check. Thank you!