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Oasst GPT Neox 20B 1000 Steps by dvruette

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Oasst GPT Neox 20B 1000 Steps is an open-source language model by dvruette. Features: 20b LLM, VRAM: 41.2GB, Context: 2K, HF Score: 42.5, LLM Explorer Score: 0.11, Arc: 48.6, HellaSwag: 74.6, MMLU: 26.4, TruthfulQA: 35.6, WinoGrande: 66.8, GSM8K: 3.1.

  Endpoints compatible   Gpt neox   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/dvruette/oasst-gpt-neox-20b-1000-steps 

Oasst GPT Neox 20B 1000 Steps Benchmarks

ARC: 48.55 vs 96.7 (so35)-49.8%
HellaSwag: 74.61 vs 95.3 (gpt4)-21.7%
MMLU: 26.39 vs 88.3 (so35)-70.1%
TruthfulQA: 35.63 vs 59 (gpt4)-39.6%
WinoGrande: 66.77 vs 87.5 (gpt4)-23.7%
GSM8K: 3.11 vs 96.4 (so35)-96.8%
LLME Score: 0.10915
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Oasst GPT Neox 20B 1000 Steps (dvruette/oasst-gpt-neox-20b-1000-steps)
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Oasst GPT Neox 20B 1000 Steps Parameters and Internals

Model Type 
Conversational AI
Use Cases 
Areas:
Research, Educational Tools, Conversational Agents
Applications:
Chatbots, Virtual Learning Assistants
Primary Use Cases:
Interactive Question Answering, Conversations with contextual understanding
Limitations:
Not suitable for decision-making in sensitive areas, Not guaranteed to be free of biases
Considerations:
Ensure proper oversight when deploying in high-stakes environments.
Additional Notes 
Encourages community contribution and feedback for ongoing development.
Training Details 
Data Sources:
Diverse internet sources, community feedback
Methodology:
Supervised fine-tuning
Model Architecture:
Modified transformer architecture optimized for dialogue.
Safety Evaluation 
Methodologies:
Red-teaming, Adversarial testing
Findings:
The model shows improved safety mechanisms and consistent behavior in following guidelines.
Risk Categories:
Misinformation, Bias
Ethical Considerations:
The model is designed with consideration toward ethical usage, avoiding generating harmful or biased content.
Responsible Ai Considerations 
Fairness:
The model adheres to fairness principles by attempting to avoid intrinsic biases present in training data.
Transparency:
OpenAssistant provides transparency reports and usage guidelines.
Accountability:
OpenAssistant is accountable for the model's outputs and continues to improve it based on community feedback.
Mitigation Strategies:
Implement ongoing model evaluations and updates based on community input.
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text with contextual understanding
Performance Tips:
Ensure prompt adherence to guidelines to maintain the intention and context.
Release Notes 
Version:
1.2
Date:
2023-08-15
Notes:
Added enhanced safety layers and improved accuracy in context retention.
LLM NameOasst GPT Neox 20B 1000 Steps
Repository 🤗https://huggingface.co/dvruette/oasst-gpt-neox-20b-1000-steps 
Model Size20b
Required VRAM41.2 GB
Updated2026-03-26
Maintainerdvruette
Model Typegpt_neox
Model Files  10.0 GB: 1-of-5   10.0 GB: 2-of-5   10.0 GB: 3-of-5   10.0 GB: 4-of-5   1.2 GB: 5-of-5
Model ArchitectureGPTNeoXForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.28.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50288
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than dvruette/oasst-gpt-neox-20b-1000-steps.

Rank the Oasst GPT Neox 20B 1000 Steps 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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