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from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
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model_id = "google/paligemma-3b-pt-224"
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model = PaliGemmaForConditionalGeneration.from_pretrained(model_id)
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processor = AutoProcessor.from_pretrained(model_id)
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breakpoint()
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prefix_output = model.language_model.forward(
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inputs_embeds=inputs_embeds[0],
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attention_mask=attention_mask,
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position_ids=position_ids,
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adarms_cond=adarms_cond[0] if adarms_cond is not None else None,
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)
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prefix_past_key_values = prefix_output.past_key_values
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# prefix_output to be used for the language head
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# shape: [batch_size, seq_len, hidden_size] with hidden_size = 2048
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prefix_output = prefix_output.last_hidden_state
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