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---
license: llama3
language:
- en
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- large language models
- speech-language models
- speech interaction
- speech-to-speech
library_name: Auto-RAG
---
# Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language models
> [Tian Yu](https://tianyu0313.github.io/), [Shaolei Zhang](https://zhangshaolei1998.github.io/), and [Yang Feng](https://people.ucas.edu.cn/~yangfeng?language=en)*
## Model Details
<!-- Provide a longer summary of what this model is. -->
- **Discription:**
- **Developed by:** ICTNLP Group. Authors: Tian Yu, Shaolei Zhang and Yang Feng.
- **Github Repository:** https://github.com/ictnlp/Auto-RAG
- **Finetuned from model:** Meta-Llama3-8B-Instruct
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
Merge the Meta-Llama3-8B-Instruct weights and Adapter weights.
```
import os
from transformers import AutoTokenizer, LlamaForCausalLM
import torch
model = LlamaForCausalLM.from_pretrained(PATH_TO_META_LLAMA3_8B_INSTRUCT,
device_map="cpu",
)
from peft import PeftModel
model = PeftModel.from_pretrained(model,
PATH_TO_ADAPTER)
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(PATH_TO_META_LLAMA3_8B_INSTRUCT)
model = model.merge_and_unload()
model.save_pretrained(SAVE_PATH)
tokenizer.save_pretrained(SAVE_PATH)
```
Subsequently, you can deploy using frameworks such as vllm.
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
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