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StructLM 34B by TIGER-Lab

 »  All LLMs  »  TIGER-Lab  »  StructLM 34B   URL Share it on

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  Arxiv:2402.16671   Autotrain compatible   Codegen   Dataset:tiger-lab/skginstruct   En   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TIGER-Lab/StructLM-34B 

StructLM 34B Benchmarks

LLME Score: 0.14722
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
StructLM 34B (TIGER-Lab/StructLM-34B)
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StructLM 34B Parameters and Internals

Model Type 
language model, structured knowledge grounding
Use Cases 
Areas:
research
Applications:
interpretation of structured data
Limitations:
May lack performance for chat applications
Additional Notes 
The 13B model uses a different prompt format than the 7B model.
Supported Languages 
en (high)
Training Details 
Data Sources:
TIGER-Lab/SKGInstruct, Open-Orca/SlimOrca
Methodology:
Finetuned with CodeLlama-Instruct-hf as base models
Input Output 
Input Format:
Specified prompt format
Accepted Modalities:
text
Output Format:
Structured outputs as per task requirements
Performance Tips:
Refer to evaluation code and setup on GitHub
LLM NameStructLM 34B
Repository 🤗https://huggingface.co/TIGER-Lab/StructLM-34B 
Model Size34b
Required VRAM67.6 GB
Updated2025-07-31
MaintainerTIGER-Lab
Model Typellama
Model Files  5.0 GB: 1-of-14   4.9 GB: 2-of-14   4.8 GB: 3-of-14   4.9 GB: 4-of-14   4.8 GB: 5-of-14   4.9 GB: 6-of-14   4.8 GB: 7-of-14   4.9 GB: 8-of-14   4.8 GB: 9-of-14   4.9 GB: 10-of-14   4.8 GB: 11-of-14   4.9 GB: 12-of-14   4.8 GB: 13-of-14   4.4 GB: 14-of-14
Supported Languagesen
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length16384
Model Max Length16384
Transformers Version4.37.2
Tokenizer ClassCodeLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

Quantized Models of the StructLM 34B

Model
Likes
Downloads
VRAM
StructLM 34B GGUF21312 GB

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CodeLlama 34B Hf16K / 67.5 GB121816
Note: green Score (e.g. "73.2") means that the model is better than TIGER-Lab/StructLM-34B.

Rank the StructLM 34B 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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Release v20241124
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