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Tiny Random Xlnet by akreal

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  Endpoints compatible   Pytorch   Region:us   Safetensors   Tf   Xlnet
Model Card on HF 🤗: https://huggingface.co/akreal/tiny-random-xlnet 

Tiny Random Xlnet Benchmarks

LLME Score: 0.001
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tiny Random Xlnet (akreal/tiny-random-xlnet)
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Tiny Random Xlnet Parameters and Internals

Model Type 
transformer, text generation
Use Cases 
Areas:
testing, educational
Applications:
demonstrations, learning
Primary Use Cases:
example for model architecture
Limitations:
not suitable for production scenarios
Considerations:
Not intended for real task processing
Additional Notes 
For educational purposes only.
Supported Languages 
English (Basic)
Training Details 
Data Sources:
synthetic data
Data Volume:
small
Methodology:
random initialization
Context Length:
128
Training Time:
few minutes
Hardware Used:
single GPU
Model Architecture:
transformer-based
Input Output 
Input Format:
plain text
Accepted Modalities:
text
Output Format:
interpreted tokens
Performance Tips:
None due to random initialization.
Release Notes 
Version:
1.0
Date:
2023-10-01
Notes:
Initial random model.
LLM NameTiny Random Xlnet
Repository 🤗https://huggingface.co/akreal/tiny-random-xlnet 
Model Size148.5k
Required VRAM0 GB
Updated2026-02-13
Maintainerakreal
Model Typexlnet
Model Files  0.0 GB   0.0 GB
Model ArchitectureAutoModel
Transformers Version4.10.0.dev0
Vocabulary Size99

Rank the Tiny Random Xlnet 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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