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Essplgpt Danube2 1 8B by sunilswain

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  Autotrain compatible   Conversational   En   Gpt   H2o-llmstudio   Mistral   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/sunilswain/essplgpt-danube2-1-8b 

Essplgpt Danube2 1 8B Benchmarks

LLME Score: 0.19807
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Essplgpt Danube2 1 8B (sunilswain/essplgpt-danube2-1-8b)

Essplgpt Danube2 1 8B Parameters and Internals

Model Type 
large language model, GPT
Training Details 
Methodology:
Trained using H2O LLM Studio
Model Architecture:
MistralForCausalLM: A transformer architecture with 24 layers, MLP, self-attention, and various linear projections. -MistralDecoderLayer for each layer (0-23). -MistralSdpaAttention for self-attention operations. -MistralMLP for multi-layer perceptron. -MistralRMSNorm for normalization. -Embedding size is 2560.
LLM NameEssplgpt Danube2 1 8B
Repository 🤗https://huggingface.co/sunilswain/essplgpt-danube2-1-8b 
Model Size8b
Required VRAM3.7 GB
Updated2025-02-22
Maintainersunilswain
Model Typemistral
Model Files  3.7 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than sunilswain/essplgpt-danube2-1-8b.

Rank the Essplgpt Danube2 1 8B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Release v20241227
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