ragler-llama2-7b

This model is a fine-tuned version of Llama2-7B described in our paper RAG-LER: Ranking Adapted Generation with Language-Model Enabled Regulation.

How to Get Started with the Model

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

tokenizer = AutoTokenizer.from_pretrained("notoookay/ragler-llama2-7b")
model = AutoModelForCausalLM.from_pretrained("notoookay/ragler-llama2-7b", torch_dtype=torch.bfloat16, device_map="auto")

# Example usage
input_text = "### Instruction:\nAnswer the following question.\n\n### Input:\nQuestion:\nWhat is the capital of France?\n\n### Response:\n"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))

The corresponding re-ranker supervised by this model can be found here.