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README.md
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license: apache-2.0
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---
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license: apache-2.0
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---
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This model is continually pre-trained from [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) with the structure proposed in [MemoryLLM](https://arxiv.org/abs/2402.04624).
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To use the model, please use the following code:
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```
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git clone [email protected]:wangyu-ustc/MemoryLLM.git
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cd MemoryLLM
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```
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Then simply use the following code to load the model:
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```python
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from modeling_memoryllm import MemoryLLM
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from configuration_memoryllm import MemoryLLMConfig
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from transformers import AutoTokenizer
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model = MemoryLLM.from_pretrained("YuWangX/memoryllm-8b-chat")
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tokenizer = AutoTokenizer.from_pretrained("YuWangX/memoryllm-8b-chat")
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```
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```python
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### How to use the model
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Inject a piece of context into the model using the following script:
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```python
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model = model.cuda()
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# Self-Update with the new context
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ctx = "David likes eating apples."
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model.inject_memory(tokenizer(ctx, return_tensors='pt', add_special_tokens=False).input_ids.cuda(), update_memory=True)
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# Generation
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messages = [{
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'role': 'user', "content": "What fruits does David like?",
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}]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
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inputs = inputs[:, 1:] # remove bos token
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outputs = model.generate(input_ids=inputs.cuda(),
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max_new_tokens=20)
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response = tokenizer.decode(outputs[0])
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outputs = model.generate(inputs=input_ids.cuda(), attention_mask=attention_mask.cuda(), max_new_tokens=10)
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print(tokenizer.decode(outputs[0]))
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```
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```
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