README.md

---
language:
- en
library_name: transformers
pipeline_tag: text-generation

base_model: meta-llama/Meta-Llama-3-8B
base_model_relation: finetune
---
# Model Information
The Llama-3-8B_SFT_Finetune_Pandas_Code is a quantized, fine-tuned version of the Meta-Llama-3 model designed specifically for analyzing tabular data.


# How to use
Starting with transformers version 4.34.0 and later, you can run conversational inference using the Transformers pipeline.

Make sure to update your transformers installation via pip install --upgrade transformers.

```python
import transformers
import torch
from peft import PeftModel, PeftConfig, get_peft_model
from transformers import pipeline
```

```python
def get_pipline():
    model_name = "nirusanan/Llama-3-8B_SFT_Finetune_Pandas_Code"

    tokenizer = AutoTokenizer.from_pretrained(model_name)
    tokenizer.pad_token = tokenizer.eos_token

    model = AutoModelForCausalLM.from_pretrained(
        model_name,
        torch_dtype=torch.float16,
        device_map="cuda:0",
        trust_remote_code=True
    )

    pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=850)

    return pipe

pipe = get_pipline()
```

```python
def generate_prompt(task, header_columns):
    prompt = f"""Below is an instruction that describes a task. Write a Python function using Pandas to accomplish the task described below.

### Instruction:
{task}

header columns with sample data:
{header_columns}

### Response:
"""
    return prompt
```

```python
prompt = generate_prompt("Your question based on tabular data", "Necessary columns names")
result = pipe(prompt)
generated_text = result[0]['generated_text']
print(generated_text.split("### End")[0])
```