--- base_model: meta-llama/Llama-3.2-1B library_name: peft pipeline_tag: text-generation tags: - base_model:adapter:meta-llama/Llama-3.2-1B - lora - sft - transformers - trl license: apache-2.0 datasets: - grasgor/steve-jobs-interviews-dpo language: - en --- # Model Card for Model ID This model is a finetuned version of Llama3.2-1B trained on Steve Jobs' interview responses. ## Model Details ### Model Description The model was trained using QLoRA. The repository contains the weights for the lora adapters and the usage is as shown below. ### Recommendations Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. ```bash from transformers import pipeline, AutoTokenizer model_name = "meta-llama/Llama-3.2-1B" # Load tokenizer tokenizer = AutoTokenizer.from_pretrained(model_name) tokenizer.pad_token = tokenizer.eos_token pipe = pipeline("text-generation", model="grasgor/jobs-llama3.2-1B-sft", tokenizer=tokenizer, return_full_text=False) prompt = "Is there an inevitable break between being an entrepreneur and a businessman? Are the people who get things going different?" result = pipe( prompt, max_new_tokens=3072, temperature=0.8, do_sample=True, top_k=50, top_p=0.9, repetition_penalty=1.2 ) print(result[0]["generated_text"]) ``` #### Response ``` The difference is that in business you're trying to make money, not something. You want your company to be successful--not just one or two individuals within it. And the reason we do this is because these are very personal endeavors for us; they have deep meaning. But if I had been able to go into my basement last night at midnight with no idea what was about to happen but know exactly where all of our chips were laid out on the table before me, would I take any chances right now? Of course! ``` - PEFT 0.16.0