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DeciLM 7B Instruct 32K by CallComply

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  Autotrain compatible   Conversational   Custom code   Dataset:open-orca/slimorca   Deci   En   Instruct   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/CallComply/DeciLM-7B-Instruct-32k 

DeciLM 7B Instruct 32K Benchmarks

LLME Score: 0.13144
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
DeciLM 7B Instruct 32K (CallComply/DeciLM-7B-Instruct-32k)
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DeciLM 7B Instruct 32K Parameters and Internals

Model Type 
Auto-regressive language model, Transformer decoder
Use Cases 
Areas:
Commercial, Research
Limitations:
Outputs may be unpredictable, inaccurate, biased, or objectionable
Considerations:
Thorough safety testing and tuning necessary for intended applications before deployment.
Additional Notes 
DeciLM-7B-instruct is optimized with AutoNAC for selection of GQA num_key_value_heads.
Supported Languages 
English (NLP)
Training Details 
Data Sources:
Open-Orca/SlimOrca
Methodology:
LoRA fine-tuning
Context Length:
32768
Model Architecture:
Transformer decoder with variable Grouped-Query Attention
Input Output 
Input Format:
Prompt templates for usage.
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Select quantization for GPUs with less than 24GB memory.
LLM NameDeciLM 7B Instruct 32K
Repository 🤗https://huggingface.co/CallComply/DeciLM-7B-Instruct-32k 
Model Size7b
Required VRAM14.1 GB
Updated2025-09-29
MaintainerCallComply
Model Typedeci
Instruction-BasedYes
Model Files  5.0 GB: 1-of-3   4.9 GB: 2-of-3   4.2 GB: 3-of-3
Supported Languagesen
Model ArchitectureDeciLMForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than CallComply/DeciLM-7B-Instruct-32k.

Rank the DeciLM 7B Instruct 32K 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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