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README.md
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Oneirogen can be used to generate novel dream narratives. It can also be used for dream analysis. For example, one could finetuned this model on [Hall and Van de Castle annotations](https://dreams.ucsc.edu/Coding/) to predict character and emotion in dream narratives. I've introduced this task in this [paper](https://aclanthology.org/2024.lrec-main.1282/).
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## Inspiration
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This model resonates with a speech called _The Android and The Human_ given by science-fiction author Philip K. Dick:
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Oneirogen can be used to generate novel dream narratives. It can also be used for dream analysis. For example, one could finetuned this model on [Hall and Van de Castle annotations](https://dreams.ucsc.edu/Coding/) to predict character and emotion in dream narratives. I've introduced this task in this [paper](https://aclanthology.org/2024.lrec-main.1282/).
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## Code
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```py
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from peft import prepare_model_for_kbit_training, PeftModel
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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import torch
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quantization_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_use_double_quant=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=torch.bfloat16,
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)
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model_id = "/gpfsdswork/projects/rech/uux/uvp47iv/notebooks/DreamLM/qwen2-7B-dream-final-merge"
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#model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=quantization_config)#, attn_implementation="flash_attention_2")#, load_in_8bits=True)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, attn_implementation="flash_attention_2")#, load_in_8bits=True)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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```
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## Inspiration
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This model resonates with a speech called _The Android and The Human_ given by science-fiction author Philip K. Dick:
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