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--- |
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license: apache-2.0 |
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datasets: |
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- lizziepika/strava_activities_runs |
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- Lukamac/MegaGym_dataset |
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language: |
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- en |
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metrics: |
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- perplexity |
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- accuracy |
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base_model: |
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- openai-community/gpt2 |
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pipeline_tag: text-generation |
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library_name: transformers |
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tags: |
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- gpt2 |
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- text-generation |
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- sports |
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- fitness |
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- gym |
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--- |
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# PlayPart AI Personal Trainer Model |
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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. |
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## Intended Use |
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- **Text Generation**: Generate text based on sports and fitness questions and interactions. |
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- **Personal Trainer Chatbot**: Suitable for chatbot integrations focused on fitness, workouts, and sports topics. |
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### Usage |
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To use the model, you can either use the Hugging Face Inference API or load it in your Python environment. |
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#### Example (Python) |
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```python |
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from transformers import GPT2Tokenizer, GPT2LMHeadModel |
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# Load the model |
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tokenizer = GPT2Tokenizer.from_pretrained("Lukamac/PlayPart-AI-Personal-Trainer") |
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model = GPT2LMHeadModel.from_pretrained("Lukamac/PlayPart-AI-Personal-Trainer") |
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# Generate a response |
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input_text = "What are the best exercises for building upper body strength?" |
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input_ids = tokenizer.encode(input_text, return_tensors='pt') |
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output_ids = model.generate(input_ids, max_length=50) |
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response = tokenizer.decode(output_ids[0], skip_special_tokens=True) |
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print(response) |
