My GPT2 is an open-source language model by qiyinmiss. Features: 137m LLM, VRAM: 0.5GB, License: mit, LLM Explorer Score: 0.15, Arc: 21.9, HellaSwag: 31.6, MMLU: 25.8, GSM8K: 0.7.
My GPT2 Parameters and Internals
Model Type transformers, language model, causal language modeling
Use Cases
Areas: research, text generation
Applications: text generation, language modeling
Primary Use Cases: generating texts from prompts
Limitations: Cannot distinguish fact from fiction, Potential bias in outputs
Considerations: Ensure deployment readiness with an understanding of biases.
Supported Languages Training Details
Data Sources: Reddit outbound links with 3+ karma
Data Volume: Over 40 GB (WebText dataset)
Methodology: Self-supervised training with causal language modeling
Context Length: Hardware Used: Model Architecture: Transformers architecture with 50,257-token vocabulary
Safety Evaluation
Ethical Considerations: Includes biases inherent to training data; caution advised for sensitive use-cases.
Responsible Ai Considerations
Fairness: Model reflects biases present in training data; conduct studies on bias in intended use cases.
Transparency: OpenAI released a model card highlighting limitations and ethical considerations.
Accountability: Deployers are responsible for usage and bias evaluation.
Mitigation Strategies: Approach deployment with caution in bias-sensitive applications; consider fine-tuning carefully.
Input Output
Input Format: Continuous text sequences
Accepted Modalities: Output Format:
Rank the My GPT2 capabilities
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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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