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TableLlama by osunlp

 »  All LLMs  »  osunlp  »  TableLlama   URL Share it on

  1118   
  Arxiv:2311.09206   Autotrain compatible   Dataset:osunlp/tableinstruct   En   Endpoints compatible   Ext 8k   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/osunlp/TableLlama 

TableLlama Benchmarks

LLME Score: 0.13862
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TableLlama (osunlp/TableLlama)
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TableLlama Parameters and Internals

Model Type 
table-based tasks, instruction tuning
Use Cases 
Areas:
research, table-based tasks
Limitations:
Performance may vary based on complexity and specifics of table tasks and datasets
Additional Notes 
Intended for open-source release supporting table tasks, acknowledging some limitations.
Supported Languages 
en (full)
Training Details 
Data Sources:
TableInstruct Dataset
Data Volume:
2.6 million table-based task data
Methodology:
LongLoRA, replacing vanilla attention with shift short attention
Context Length:
8000
Training Time:
9 days
Hardware Used:
48 80*A100 cluster
Input Output 
Input Format:
Instruction, Input, Question
Accepted Modalities:
text
Output Format:
Response text
LLM NameTableLlama
Repository 🤗https://huggingface.co/osunlp/TableLlama 
Model Size7b
Required VRAM13.5 GB
Updated2025-08-22
Maintainerosunlp
Model Typellama
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2   0.0 GB
Supported Languagesen
Context Length8k
Model ArchitectureLlamaForCausalLM
Licensecc-by-4.0
Context Length4096
Model Max Length4096
Transformers Version4.33.2
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32001
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than osunlp/TableLlama.

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