Instructions to use mayankchugh-learning/gpt2-lora-ai-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mayankchugh-learning/gpt2-lora-ai-demo with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("gpt2") model = PeftModel.from_pretrained(base_model, "mayankchugh-learning/gpt2-lora-ai-demo") - Notebooks
- Google Colab
- Kaggle
GPT-2 + LoRA Fine-Tuned (AI Demo)
Fine-tuned with PEFT/LoRA on a small AI Q&A corpus.
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained("gpt2")
model = PeftModel.from_pretrained(base, "mayankchugh-learning/gpt2-lora-ai-demo")
tok = AutoTokenizer.from_pretrained("mayankchugh-learning/gpt2-lora-ai-demo")
inputs = tok("Hugging Face is", return_tensors="pt")
output = model.generate(**inputs, max_new_tokens=40)
print(tok.decode(output[0]))
Training
- Base model : gpt2
- LoRA rank : 8
- Epochs : 2
- Created by : mayankchugh-learning
- Downloads last month
- 6
Model tree for mayankchugh-learning/gpt2-lora-ai-demo
Base model
openai-community/gpt2