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DeciLM 7B Instruct 128K by CallComply

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Model Card on HF 🤗: https://huggingface.co/CallComply/DeciLM-7B-Instruct-128k 

DeciLM 7B Instruct 128K Benchmarks

LLME Score: 0.1358
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 128K (CallComply/DeciLM-7B-Instruct-128k)
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DeciLM 7B Instruct 128K Parameters and Internals

Model Type 
auto-regressive language model
Use Cases 
Areas:
commercial, research
Supported Languages 
en (NLP)
Training Details 
Data Sources:
Open-Orca/SlimOrca
Methodology:
LoRA fine-tuning
Context Length:
8192
Model Architecture:
optimized transformer decoder with variable Grouped-Query Attention
Safety Evaluation 
Ethical Considerations:
DeciLM-7B-instruct is a new technology that comes with inherent risks associated with its use. The testing conducted so far does not encompass all possible scenarios. Outputs are unpredictable, and the model may generate inaccurate, biased, or objectionable responses.
LLM NameDeciLM 7B Instruct 128K
Repository 🤗https://huggingface.co/CallComply/DeciLM-7B-Instruct-128k 
Model Size7b
Required VRAM14.1 GB
Updated2025-08-19
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 Length131072
Model Max Length131072
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-128k.

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Instruction Following and Task Automation  
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Release v20241124
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