Instructions to use rahuldhole/tiny-llm-qwen-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rahuldhole/tiny-llm-qwen-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "rahuldhole/tiny-llm-qwen-adapter") - Notebooks
- Google Colab
- Kaggle
Tiny LLM
Author: Rahul Dhole Base Model: Qwen/Qwen2.5-0.5B-Instruct
Tiny LLM is a fine-tuned language model by Rahul Dhole, built on top of Qwen2.5-0.5B-Instruct using LoRA/PEFT.
Training
- Method: LoRA (r=8, alpha=32)
- Epochs: 10
- Learning Rate: 0.001
- Data: data/dummy_train.jsonl
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