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RCC Ins Reconstruction by fcyp

 »  All LLMs  »  fcyp  »  RCC Ins Reconstruction   URL Share it on

  12   
  Arxiv:2406.06110   Autotrain compatible   Endpoints compatible   Gpt neox   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/fcyp/RCC_Ins_Reconstruction 

RCC Ins Reconstruction Benchmarks

LLME Score: 0.17591
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
RCC Ins Reconstruction (fcyp/RCC_Ins_Reconstruction)

RCC Ins Reconstruction Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
QA tasks
Limitations:
Performance may degrade for sequences longer than the fine-tuning dataset length
Additional Notes 
Employs FlashAttention-2.
Training Details 
Methodology:
Recurrent Context Compression (RCC)
Context Length:
2048
Model Architecture:
Encoder-decoder based; Transformer for the decoder
Input Output 
Input Format:
text prompt
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Add specific code to prevent running out of memory during model evaluation.
Release Notes 
Version:
RCC-Pythia-1.4b
Date:
2024/6/10
Notes:
Released the RCC-Pythia-1.4b model and related paper
LLM NameRCC Ins Reconstruction
Repository 🤗https://huggingface.co/fcyp/RCC_Ins_Reconstruction 
Model Size1.4b
Required VRAM6.1 GB
Updated2025-06-01
Maintainerfcyp
Model Typegpt_neox
Model Files  5.0 GB: 1-of-2   1.1 GB: 2-of-2
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.40.2
Vocabulary Size50304
Torch Data Typebfloat16

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

Rank the RCC Ins Reconstruction 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 v20241227
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