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StructLM 7B by TIGER-Lab

 »  All LLMs  »  TIGER-Lab  »  StructLM 7B   URL Share it on

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  Arxiv:2402.16671   Autotrain compatible   Codegen   Conversational   Dataset:tiger-lab/skginstruct   En   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TIGER-Lab/StructLM-7B 

StructLM 7B Benchmarks

LLME Score: 0.13903
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
StructLM 7B (TIGER-Lab/StructLM-7B)
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StructLM 7B Parameters and Internals

Model Type 
text generation, structured knowledge grounding
Use Cases 
Limitations:
May lack performance for chat applications
Supported Languages 
en (unknown)
Training Details 
Data Sources:
SKGInstruct Dataset, SlimOrca
Methodology:
Fine-tuning
Input Output 
Input Format:
Structured information inputs with specified tasks
Output Format:
Strict adherence to specified output format
LLM NameStructLM 7B
Repository 🤗https://huggingface.co/TIGER-Lab/StructLM-7B 
Model Size7b
Required VRAM13.5 GB
Updated2025-09-23
MaintainerTIGER-Lab
Model Typellama
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   3.6 GB: 3-of-3
Supported Languagesen
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length16384
Model Max Length16384
Transformers Version4.45.0
Tokenizer ClassCodeLlamaTokenizer
Padding Token</s>
Vocabulary Size32016
Torch Data Typebfloat16

Quantized Models of the StructLM 7B

Model
Likes
Downloads
VRAM
StructLM 7B GGUF31022 GB

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Note: green Score (e.g. "73.2") means that the model is better than TIGER-Lab/StructLM-7B.

Rank the StructLM 7B 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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