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---
license: llama2
language:
- en
- ar
metrics:
- accuracy
- f1
library_name: transformers
---
# llama-7b-v1-Receipt-Key-Extraction
llama-7b-v1-Receipt-Key-Extraction is a 7 billion parameter based on LLamA v1
[AMuRD: Annotated Multilingual Receipts Dataset for Cross-lingual Key Information Extraction and Classification
](https://arxiv.org/abs/2309.09800)
## Uses
The model is intended for research-only use in English and Arabic for key information extraction for items in receipts.
## How to Get Started with the Model
Use the code below to get started with the model.
```bibtex
# pip install -q transformers
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
checkpoint = "abdoelsayed/llama-7b-v1-Receipt-Key-Extraction"
device = "cuda" if torch.cuda.is_available() else "cpu"
tokenizer = AutoTokenizer.from_pretrained(checkpoint, model_max_length=512,
padding_side="right",
use_fast=False,)
model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
def generate_response(instruction, input_text, max_new_tokens=100, temperature=0.1, num_beams=4 ,top_k=40):
prompt = f"Below is an instruction that describes a task, paired with an input that provides further context.\n\n### Instruction:\n{instruction}\n\n### Input:\n{input_text}\n\n### Response:"
inputs = tokenizer(prompt, return_tensors="pt")
input_ids = inputs["input_ids"].to(device)
generation_config = GenerationConfig(
temperature=temperature,
top_p=top_p,
top_k=top_k,
num_beams=num_beams,
)
with torch.no_grad():
outputs = model.generate(input_ids,generation_config=generation_config, max_new_tokens=max_new_tokens)
outputs = tokenizer.decode(outputs.sequences[0])
return output.split("### Response:")[-1].strip().replace("</s>","")
instruction = "Extract the class, Brand, Weight, Number of units, Size of units, Price, T.Price, Pack, Unit from the following sentence"
input_text = "Americana Okra zero 400 gm"
response = generate_response(instruction, input_text)
print(response)
```
## How to Cite
Please cite this model using this format.
```bibtex
@misc{abdallah2023amurd,
title={AMuRD: Annotated Multilingual Receipts Dataset for Cross-lingual Key Information Extraction and Classification},
author={Abdelrahman Abdallah and Mahmoud Abdalla and Mohamed Elkasaby and Yasser Elbendary and Adam Jatowt},
year={2023},
eprint={2309.09800},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
``` |