mistral_wwetrivia

Mistral WWE GGUF Model

Welcome to the Mistral WWE GGUF model repository! This model has been fine-tuned on WWE-related trivia data and is designed to generate multiple-choice questions and answers in the context of WWE events, superstars, and history.

Model Details

• Model Name: Mistral WWE GGUF
• Model Architecture: Mistral
• Model Type: Causal Language Model
• Training Data: Fine-tuned on a custom dataset of WWE-related trivia.
• Format: GGUF (General Graph Universal Format)

Usage

Installation

To use this model, you will need the transformers and llama_cpp libraries installed. You can install them using pip:

pip install transformers llama_cpp

from transformers import AutoTokenizer
from llama_cpp import Llama

model_path = "path/to/gguf_model"

model = Llama(model_path=model_path)

input_text = "Who won the first Royal Rumble in 1988?"

# Generate output
output = model(input_text, max_tokens=8000)  
result = output['choices'][0]

text = result['text']
print(text)

Question: Who won the first Royal Rumble in 1988?
Options:
a: Jim Duggan
b: Hulk Hogan
c: Randy Savage
d: Andre the Giant
Correct Answer: a: Jim Duggan

Training

The model was fine-tuned on a custom dataset consisting of WWE trivia questions. The fine-tuning process involved training the model for 10 epochs using a batch size of 16 on a single GPU.

Hyperparameters

• Learning Rate: 2e-4
• Batch Size: 16
• Number of Epochs: 10
• Optimizer: AdamW

Model Performance

The model has been evaluated on a validation set of WWE trivia questions, achieving an accuracy of 95% on multiple-choice questions.

Limitations and Biases

• Domain Specific: The model is fine-tuned specifically for WWE-related trivia and may not perform well on general knowledge questions.
• Bias: The model may reflect biases present in the training data.

Citation

@misc{mistral_wwe_trivia_2024,
  author = {Saahil97},
  title = {Mistral WWE GGUF Model},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/Saahil97/mistral_wwetrivia}
}