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Llama2 0B Unit Test by MaxJeblick

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  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/MaxJeblick/llama2-0b-unit-test 

Llama2 0B Unit Test Benchmarks

LLME Score: 0.13857
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Llama2 0B Unit Test Parameters and Internals

Model Type 
text generation, causal language model
Use Cases 
Areas:
Testing
Applications:
Unit Testing, Integration Testing
Considerations:
Suitable for environments with CPU only hardware.
Training Details 
Methodology:
Modified LLama2 configuration
Context Length:
1024
Model Architecture:
Customized with hidden size of 12, 1024 max position embeddings, 2 hidden layers, 2 attention heads
Input Output 
Input Format:
input_ids from model.dummy_inputs
Accepted Modalities:
text
Output Format:
token generation
Performance Tips:
Use fixtures with session scope for loading the model to reduce test runtime.
LLM NameLlama2 0B Unit Test
Repository 🤗https://huggingface.co/MaxJeblick/llama2-0b-unit-test 
Model Size0b
Required VRAM0 GB
Updated2025-06-09
MaintainerMaxJeblick
Model Typellama
Model Files  0.0 GB   0.0 GB
Model ArchitectureLlamaForCausalLM
Context Length1024
Model Max Length1024
Transformers Version4.38.1
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
Llama2 0B Unit Test (MaxJeblick/llama2-0b-unit-test)

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Note: green Score (e.g. "73.2") means that the model is better than MaxJeblick/llama2-0b-unit-test.

Rank the Llama2 0B Unit Test 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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Release v20241124
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