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Aira OPT 350M by nicholasKluge

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Aira OPT 350M is an open-source language model by nicholasKluge. Features: 350m LLM, Context: 2K, License: other, Instruction-Based, LLM Explorer Score: 0.1.

  Arxiv:1803.05457   Arxiv:2109.07958   Arxiv:2203.09509   Alignment   Assistant   Autotrain compatible   Base model:facebook/opt-350m Base model:finetune:facebook/o...   Co2 eq emissions   Conversation Dataset:nicholaskluge/instruct...   En   Endpoints compatible   Instruct   Opt   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/nicholasKluge/Aira-OPT-350M 

Aira OPT 350M Benchmarks

LLME Score: 0.10196
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Aira OPT 350M (nicholasKluge/Aira-OPT-350M)
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Aira OPT 350M Parameters and Internals

Model Type 
text generation, instruction tuned, conversation, assistant
Additional Notes 
The model may produce hallucinations, biases, and get stuck in repetition loops.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
nicholasKluge/instruct-aira-dataset
Methodology:
Fine-tuning
Hardware Used:
1 NVIDIA A100-SXM4-40GB
Input Output 
Input Format:
Special tokens used: <|startofinstruction|>, <|endofinstruction|>, <|endofcompletion|>
Accepted Modalities:
text
Output Format:
Generated text response.
Performance Tips:
No specific tips provided.
LLM NameAira OPT 350M
Repository 🤗https://huggingface.co/nicholasKluge/Aira-OPT-350M 
Base Model(s)  Opt 350M   facebook/opt-350m
Model Size350m
Required VRAM0 GB
Updated2025-09-23
MaintainernicholasKluge
Model Typeopt
Instruction-BasedYes
Model Files  1.3 GB   2.6 GB   1.3 GB   0.0 GB   0.0 GB
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.34.1
Tokenizer ClassGPT2Tokenizer
Padding Token<|pad|>
Vocabulary Size50270
Torch Data Typefloat32
Activation Functionrelu
Errorsreplace

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Opt 350M Instruct2K / 1.3 GB204
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Rank the Aira OPT 350M 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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