---
library_name: peft
base_model: TheBloke/Llama-2-7b-Chat-GPTQ
pipeline_tag: text-generation
inference: false
license: openrail
language:
- en
datasets:
- flytech/python-codes-25k
tags:
- text2code
- LoRA
- GPTQ
- Llama-2-7B-Chat
- text2python
- instruction2code
---

# Llama-2-7b-Chat-GPTQ fine-tuned on PYTHON-CODES-25K

Generate Python code that accomplishes the task instructed.


## LoRA Adpater Head

### Description

Parameter Efficient Finetuning(PEFT) a 4bit quantized Llama-2-7b-Chat from TheBloke/Llama-2-7b-Chat-GPTQ on flytech/python-codes-25k dataset.

- **Language(s) (NLP):** English
- **License:** openrail
- **Qunatization:** GPTQ 4bit
- **PEFT:** LoRA
- **Finetuned from model [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GPTQ)**
- **Dataset:** [flytech/python-codes-25k](https://huggingface.co/datasets/flytech/python-codes-25k)

## Intended uses & limitations

Addressing the efficay of Quantization and PEFT. Implemented as a personal Project.

### How to use

The quantized model is finetuned as PEFT. We have the trained Adapter. <br>The trained adpated needs to be merged with Base Model on which it was trained.

```python
instruction = """model_input = "Help me set up my daily to-do list!""""
```
```python
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM

config = PeftConfig.from_pretrained("SwastikM/Llama-2-7B-Chat-text2code")
model = AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-7b-Chat-GPTQ")
model = PeftModel.from_pretrained(model, "SwastikM/Llama-2-7B-Chat-text2code")
tokenizer = AutoTokenizer.from_pretrained("SwastikM/Llama-2-7B-Chat-text2code")

inputs = tokenizer(instruction, return_tensors="pt").input_ids.to('cuda')
outputs = model.generate(inputs, max_new_tokens=500, do_sample=False, num_beams=1)
code = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(code)
```


## Training Details

### Training Data

[gretelai/synthetic_text_to_sql](https://huggingface.co/datasets/gretelai/synthetic_text_to_sql)

### Training Procedure

HuggingFace Accelerate with Training Loop.

#### Preprocessing 

- ***Encoder Input:*** "sql_prompt: " + data['sql_prompt']+" sql_context: "+data['sql_context']
- ***Decoder Input:*** data['sql']


#### Training Hyperparameters

- **Optimizer:** AdamW
- **lr:** 2e-5
- **decay:** linear
- **num_warmup_steps:** 0
- **batch_size:** 8
- **num_training_steps:** 12500


#### Hardware

- **GPU:** P100


### Citing Dataset and BaseModel

```
  @software{gretel-synthetic-text-to-sql-2024,
  author = {Meyer, Yev and Emadi, Marjan and Nathawani, Dhruv and Ramaswamy, Lipika and Boyd, Kendrick and Van Segbroeck, Maarten and Grossman, Matthew and Mlocek, Piotr and Newberry, Drew},
  title = {{Synthetic-Text-To-SQL}: A synthetic dataset for training language models to generate SQL queries from natural language prompts},
  month = {April},
  year = {2024},
  url = {https://huggingface.co/datasets/gretelai/synthetic-text-to-sql}
}
```

```
@article{DBLP:journals/corr/abs-1910-13461,
  author    = {Mike Lewis and
               Yinhan Liu and
               Naman Goyal and
               Marjan Ghazvininejad and
               Abdelrahman Mohamed and
               Omer Levy and
               Veselin Stoyanov and
               Luke Zettlemoyer},
  title     = {{BART:} Denoising Sequence-to-Sequence Pre-training for Natural Language
               Generation, Translation, and Comprehension},
  journal   = {CoRR},
  volume    = {abs/1910.13461},
  year      = {2019},
  url       = {http://arxiv.org/abs/1910.13461},
  eprinttype = {arXiv},
  eprint    = {1910.13461},
  timestamp = {Thu, 31 Oct 2019 14:02:26 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1910-13461.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

```

## Additional Information

- ***Github:*** [Repository](https://github.com/swastikmaiti/SwastikM-bart-large-nl2sql.git)

## Acknowledgment

Thanks to [@AI at Meta](https://huggingface.co/facebook) for adding the Pre Trained Model.
Thanks to [@Gretel.ai](https://huggingface.co/gretelai) for adding the datset.


## Model Card Authors

Swastik Maiti