| language: en | |
| license: apache-2.0 | |
| tags: | |
| - lora | |
| - adapter | |
| # LoRA Adapter for [Base Model Name] | |
| This is a LoRA adapter trained on [describe your training data and task]. | |
| ## Usage | |
| To use this adapter: | |
| ```python | |
| from peft import PeftModel, PeftConfig | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| base_model_name = "base_model_name" | |
| adapter_name = "your-username/your-lora-adapter-name" | |
| # Load base model | |
| base_model = AutoModelForCausalLM.from_pretrained(base_model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(base_model_name) | |
| # Load LoRA adapter | |
| model = PeftModel.from_pretrained(base_model, adapter_name) | |
| # Use the model | |
| input_text = "Your input text here" | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| outputs = model.generate(**inputs) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| ``` | |