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Update README.md

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@@ -15,11 +15,10 @@ cd MemoryLLM
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  Then simply use the following code to load the model:
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  ```python
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  import torch
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- from modeling_memoryllm import MemoryLLM
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  from transformers import AutoTokenizer
 
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  # load the model mplus-8b (currently we only have the pretrained version)
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- from modeling_mplus import MPlus
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  model = MPlus.from_pretrained("YuWangX/mplus-8b", attn_implementation="flash_attention_2", torch_dtype=torch.bfloat16)
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  tokenizer = AutoTokenizer.from_pretrained("YuWangX/mplus-8b")
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  model = model.to(torch.bfloat16) # need to call it again to cast the `inv_freq` in rotary_emb to bfloat16 as well
 
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  Then simply use the following code to load the model:
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  ```python
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  import torch
 
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  from transformers import AutoTokenizer
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+ from modeling_mplus import MPlus
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  # load the model mplus-8b (currently we only have the pretrained version)
 
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  model = MPlus.from_pretrained("YuWangX/mplus-8b", attn_implementation="flash_attention_2", torch_dtype=torch.bfloat16)
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  tokenizer = AutoTokenizer.from_pretrained("YuWangX/mplus-8b")
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  model = model.to(torch.bfloat16) # need to call it again to cast the `inv_freq` in rotary_emb to bfloat16 as well