Gpt2 Large is an open-source language model by openai-community. Features: 811.8m LLM, VRAM: 3.2GB, License: mit, LLM Explorer Score: 0.16, Arc: 25.8, HellaSwag: 45.6, MMLU: 26.1, GSM8K: 0.8.
Gpt2 Large Parameters and Internals
Model Type Transformer-based language model
Use Cases
Areas: Applications: Text generation, Writing assistance, Creative writing, Entertainment
Primary Use Cases: AI research and understanding generative language models
Limitations: Certain sensitive and bias-prone applications
Considerations: Awareness of biases and reliability in factual text generation.
Additional Notes The model card highlights that significant caution is to be taken with content bias and ethical deployment considerations.
Supported Languages Training Details
Data Sources: Data Volume: Methodology: Pretrained on a large corpus of English data in a self-supervised manner (causal language modeling - CLM)
Context Length: Model Architecture:
Safety Evaluation
Methodologies: Zero-shot and context-aware evaluations
Findings: Contains biases inherent to training data
Risk Categories: Bias in generated predictions
Ethical Considerations: Bias awareness and risk evaluations for sensitive human attributes
Responsible Ai Considerations
Fairness: Potential biases in generation across protected classes and groups.
Transparency: Model's behavior and biases are noted but not fully transparent given training data sources.
Accountability: OpenAI is accountable for model and its releases.
Mitigation Strategies: Bias analyses and user awareness recommendations.
Input Output
Input Format: PyTorch and TensorFlow pipelines
Accepted Modalities: Output Format: Performance Tips: Potential bias and misuse caution advised.
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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