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ICKG V3.2 by victorlxh

 »  All LLMs  »  victorlxh  »  ICKG V3.2   URL Share it on

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  Arxiv:2310.06825   Arxiv:2407.10909   Adapter   Finetuned   Lora   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/victorlxh/ICKG-v3.2 

ICKG V3.2 Benchmarks

LLME Score: 0.15871
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
ICKG V3.2 (victorlxh/ICKG-v3.2)

ICKG V3.2 Parameters and Internals

Model Type 
Auto-regressive language model, Transformer architecture
Use Cases 
Areas:
Research, Natural language processing, Knowledge graph construction
Applications:
Generating knowledge graphs, Aspect-Based Sentiment Analysis
Primary Use Cases:
Generative Knowledge Graph Construction, Aspect-Based Sentiment Analysis
Additional Notes 
ICKG excels in generating instruction-based knowledge graphs emphasizing quality and adherence to format.
Training Details 
Data Volume:
~5K instruction-following demonstrations
Model Architecture:
Transformer architecture
LLM NameICKG V3.2
Repository 🤗https://huggingface.co/victorlxh/ICKG-v3.2 
Required VRAM0 GB
Updated2025-02-22
Maintainervictorlxh
Model Files  0.0 GB
Model ArchitectureAdapter
Licensecc-by-nc-4.0
Model Max Length8192
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|q_proj
LoRA Alpha16
LoRA Dropout0.05
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than victorlxh/ICKG-v3.2.

Rank the ICKG V3.2 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 v20241227
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