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Instruct GPT by Sharathhebbar24

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Instruct GPT is an open-source language model by Sharathhebbar24. Features: LLM, VRAM: 1.4GB, License: mit, Instruction-Based, LLM Explorer Score: 0.15, Arc: 28.2, HellaSwag: 39.3, MMLU: 26.8, GSM8K: 0.3.

Dataset:databricks/databricks-...   En   Endpoints compatible   Gpt2   Gpt2-medium   Instruct   Model-index   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/Sharathhebbar24/Instruct_GPT 

Instruct GPT Benchmarks

ARC: 28.24 vs 96.7 (so35)-70.8%
HellaSwag: 39.33 vs 95.3 (gpt4)-58.7%
MMLU: 26.84 vs 88.3 (so35)-69.6%
GSM8K: 0.3 vs 96.4 (so35)-99.7%
LLME Score: 0.15311
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Instruct GPT (Sharathhebbar24/Instruct_GPT)
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Instruct GPT Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model is a finetuned version of `gpt2-medium`.
Training Details 
Data Sources:
databricks/databricks-dolly-15k
LLM NameInstruct GPT
Repository 🤗https://huggingface.co/Sharathhebbar24/Instruct_GPT 
Required VRAM1.4 GB
Updated2026-05-01
MaintainerSharathhebbar24
Model Typegpt2
Instruction-BasedYes
Model Files  1.4 GB
Supported Languagesen
Model ArchitectureGPT2LMHeadModel
Licensemit
Model Max Length1024
Transformers Version4.34.1
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than Sharathhebbar24/Instruct_GPT.

Rank the Instruct GPT Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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