LLaMA 3 8B - Career Counseling Model

Model Description

This is a fine-tuned version of the LLaMA 3 8B model, designed to assist users in career-related inquiries. The model provides personalized career advice, guidance on education paths, and insights into job opportunities based on the user’s input.

Base Model: LLaMA 3 8B
Fine-Tuned On: Career counseling dataset (or specify other datasets)
Model Type: Causal Language Model (CLM)

Intended Use

This model is intended to assist users by offering insights and recommendations related to their career choices, job applications, and educational paths. It is designed to answer career-related queries, provide suggestions, and guide users in their professional journeys.

Use Cases:

Career counseling chatbots.
Educational guidance apps.
Job application and resume assistance.

Limitations:

Not a replacement for professional career coaching: The model provides general advice and should not be solely relied on for critical career decisions.
Language Bias: The model may exhibit biases based on the training data.

How to Use

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the fine-tuned model and tokenizer
model = AutoModelForCausalLM.from_pretrained("your_username/career-counseling-model")
tokenizer = AutoTokenizer.from_pretrained("your_username/career-counseling-model")

# Generate text
inputs = tokenizer("What are the best career options for a software engineer?", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0]))