# aaa-2-sql

This is a finetuned version of [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) using LoRA with LitGPT.

## Training Details

- **Base Model:** mistralai/Mistral-7B-Instruct-v0.3
- **Framework:** LitGPT
- **Finetuning Method:** Low-Rank Adaptation (LoRA)
- **LoRA Parameters:**
  - Rank (r): 16
  - Alpha: 32
  - Dropout: 0.05
- **Quantization:** bnb.nf4
- **Context Length:** 4098 tokens
- **Training Steps:** 2000

## Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("exaler/aaa-2-sql")
tokenizer = AutoTokenizer.from_pretrained("exaler/aaa-2-sql")

# Create prompt
prompt = "Your prompt here"

# Generate text
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=1024)
response = tokenizer.decode(output[0], skip_special_tokens=True)
print(response)
```