metadata

license: apache-2.0
datasets:
  - lizziepika/strava_activities_runs
  - Lukamac/MegaGym_dataset
language:
  - en
metrics:
  - perplexity
  - accuracy
base_model:
  - openai-community/gpt2
pipeline_tag: text-generation
library_name: transformers
tags:
  - gpt2
  - text-generation
  - sports
  - fitness
  - gym

PlayPart AI Personal Trainer Model

This model is a fine-tuned version of GPT-2, specifically trained on sports-related and gym exercise datasets. It is intended to provide text-generation capabilities for answering questions about fitness, sports, workout routines, and providing personalized training suggestions.

Intended Use

Text Generation: Generate text based on sports and fitness questions and interactions.
Personal Trainer Chatbot: Suitable for chatbot integrations focused on fitness, workouts, and sports topics.

Usage

To use the model, you can either use the Hugging Face Inference API or load it in your Python environment.

Example (Python)

from transformers import GPT2Tokenizer, GPT2LMHeadModel

# Load the model
tokenizer = GPT2Tokenizer.from_pretrained("Lukamac/PlayPart-AI-Personal-Trainer")
model = GPT2LMHeadModel.from_pretrained("Lukamac/PlayPart-AI-Personal-Trainer")

# Generate a response
input_text = "What are the best exercises for building upper body strength?"
input_ids = tokenizer.encode(input_text, return_tensors='pt')
output_ids = model.generate(input_ids, max_length=50)
response = tokenizer.decode(output_ids[0], skip_special_tokens=True)

print(response)