fix for max sequence len across different model types
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@@ -255,8 +255,15 @@ def load_model(
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)
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# Shouldn't be a problem most of the time. will obviously error if the model doesn't support this
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# when training starts
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if config.max_seq_len and cfg.sequence_len > config.max_seq_len:
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if hasattr(config, "max_seq_len") and cfg.sequence_len > config.max_seq_len:
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config.max_seq_len = cfg.sequence_len
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logging.warning(f"increasing context length to {cfg.sequence_len}")
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elif (
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hasattr(config, "max_sequence_length")
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and cfg.sequence_len > config.max_sequence_length
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):
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config.max_sequence_length = cfg.sequence_len
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logging.warning(f"increasing context length to {cfg.sequence_len}")
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model = AutoModelForCausalLM.from_pretrained(
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base_model,
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config=config,
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