---
license: mit
language:
- en
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
---

# 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

```python
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]))