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LIMA 13B by heegyu

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LIMA 13B is an open-source language model by heegyu. Features: 13b LLM, VRAM: 42GB, License: other, LLM Explorer Score: 0.09.

  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/heegyu/LIMA-13b 

LIMA 13B Benchmarks

LLME Score: 0.09414
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LIMA 13B (heegyu/LIMA-13b)
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LIMA 13B Parameters and Internals

Model Type 
auto-regressive, transformer architecture
Use Cases 
Primary Use Cases:
Research on large language models, Exploring applications such as question answering and reading comprehension, Evaluating and mitigating biases, Determining capabilities and limitations of models
Limitations:
Base model not suitable for downstream applications without risk evaluation
Supported Languages 
en (High proficiency), others (Included 20 languages, mainly supports English)
Training Details 
Data Sources:
CCNet, C4, GitHub, Wikipedia, Books, ArXiv, Stack Exchange
Data Volume:
1T tokens with different breakdowns for different model sizes
Model Architecture:
transformer architecture
Responsible Ai Considerations 
Fairness:
Model reflects biases from web sources. Evaluated biases include gender, religion, race, sexual orientation, age, nationality, disability, physical appearance, and socioeconomic status.
Transparency:
Model trained using web-sourced data which may contain biased and harmful content.
Accountability:
Use GitHub repository to raise questions or comments.
Mitigation Strategies:
Filtered data based on proximity to Wikipedia text using a Kneser-Ney language model and fastText linear classifier.
LLM NameLIMA 13B
Repository 🤗https://huggingface.co/heegyu/LIMA-13b 
Model Size13b
Required VRAM42 GB
Updated2025-09-23
Maintainerheegyu
Model Typellama
Model Files  1.0 GB: 0-of-41   1.0 GB: 1-of-41   1.0 GB: 2-of-41   1.0 GB: 3-of-41   1.0 GB: 4-of-41   1.0 GB: 5-of-41   1.0 GB: 6-of-41   1.0 GB: 7-of-41   1.0 GB: 8-of-41   1.0 GB: 9-of-41   1.0 GB: 10-of-41   1.0 GB: 11-of-41   1.0 GB: 12-of-41   1.0 GB: 13-of-41   1.0 GB: 14-of-41   1.0 GB: 15-of-41   1.0 GB: 16-of-41   1.0 GB: 17-of-41   1.0 GB: 18-of-41   1.0 GB: 19-of-41   1.0 GB: 20-of-41   1.0 GB: 21-of-41   1.0 GB: 22-of-41   1.0 GB: 23-of-41   1.0 GB: 24-of-41   1.0 GB: 25-of-41   1.0 GB: 26-of-41   1.0 GB: 27-of-41   1.0 GB: 28-of-41   1.0 GB: 29-of-41   1.0 GB: 30-of-41   1.0 GB: 31-of-41   1.0 GB: 32-of-41   1.0 GB: 33-of-41   1.0 GB: 34-of-41   1.0 GB: 35-of-41   1.0 GB: 36-of-41   1.0 GB: 37-of-41   1.0 GB: 38-of-41   1.0 GB: 39-of-41   1.0 GB: 40-of-41   1.0 GB: 41-of-41
Model ArchitectureLLaMAForCausalLM
Licenseother
Transformers Version4.27.0.dev0
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than heegyu/LIMA-13b.

Rank the LIMA 13B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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