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Gpt2 Xl Lima by lgaalves

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Gpt2 Xl Lima is an open-source language model by lgaalves. Features: 1.6b LLM, VRAM: 3.1GB, License: mit, LLM Explorer Score: 0.15, Arc: 31.1, HellaSwag: 51.3, MMLU: 25.4, GSM8K: 0.9.

  Dataset:gair/lima   En   Endpoints compatible   Gpt2   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/lgaalves/gpt2-xl_lima 

Gpt2 Xl Lima Benchmarks

ARC: 31.14 vs 96.7 (so35)-67.8%
HellaSwag: 51.28 vs 95.3 (gpt4)-46.2%
MMLU: 25.43 vs 88.3 (so35)-71.2%
GSM8K: 0.91 vs 96.4 (so35)-99.1%
LLME Score: 0.14938
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gpt2 Xl Lima (lgaalves/gpt2-xl_lima)
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Gpt2 Xl Lima Parameters and Internals

Model Type 
auto-regressive, language model
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
text generation
Limitations:
may produce false information, contains unfiltered content from the internet
Supported Languages 
en (proficient)
Training Details 
Data Sources:
GAIR/lima
Methodology:
instruction fine-tuning using LoRA
Training Time:
10 minutes
Hardware Used:
1 Tesla V100-SXM2-16GB
Model Architecture:
GPT-2 transformer architecture
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NameGpt2 Xl Lima
Repository 🤗https://huggingface.co/lgaalves/gpt2-xl_lima 
Model Size1.6b
Required VRAM3.1 GB
Updated2026-05-23
Maintainerlgaalves
Model Typegpt2
Model Files  3.1 GB   3.1 GB
Supported Languagesen
Model ArchitectureGPT2LMHeadModel
Licensemit
Model Max Length1024
Transformers Version4.34.0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50257
Torch Data Typefloat16
Activation Functiongelu_new

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Note: green Score (e.g. "73.2") means that the model is better than lgaalves/gpt2-xl_lima.

Rank the Gpt2 Xl Lima 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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