---
license: apache-2.0
tags:
- text-generation
- gpt2
- lora
- fine-tuned
datasets:
- private
base_model: gpt2
model-index:
- name: tea-gpt2-lora-sft
  results: []
---

# tea-gpt2-lora-sft

## Model Description

This model is a **LoRA fine-tuned GPT-2** model using the [PEFT library](https://huggingface.co/docs/peft/index). It was trained on a domain-specific dataset related to [insert topic here, e.g., "tea conversations", "Sri Lankan literature", etc.].

- **Base model**: [`gpt2`](https://huggingface.co/gpt2)
- **Fine-tuning method**: Low-Rank Adaptation (LoRA)
- **Framework**: Hugging Face Transformers + PEFT
- **Quantization**: [if applicable, e.g., int8, bf16]

## Intended Use

You can use this model for:

- Text generation in tea cultivation industry
- Creative writing or domain-specific chatbots

## How to Use

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

base_model = AutoModelForCausalLM.from_pretrained("gpt2")
lora_model = PeftModel.from_pretrained(base_model, "nimeth02/tea-gpt2-lora-sft")
tokenizer = AutoTokenizer.from_pretrained("gpt2")

input_text = "Once upon a time in a tea garden"
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
output = lora_model.generate(input_ids, max_new_tokens=50)

print(tokenizer.decode(output[0], skip_special_tokens=True))