jobs-llama3.2-1B-sft

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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.

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Recommendations

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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.

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!

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• PEFT 0.16.0