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Opt 350M by facebook

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  114715   
  Arxiv:2005.14165   Arxiv:2205.01068   Autotrain compatible   En   Jax   Opt   Pytorch   Region:us   Tf
Model Card on HF 🤗: https://huggingface.co/facebook/opt-350m 

Opt 350M Benchmarks

ARC: 23.55 vs 96.7 (so35)-75.6%
HellaSwag: 36.73 vs 95.3 (gpt4)-61.5%
MMLU: 26.02 vs 88.3 (so35)-70.5%
TruthfulQA: 40.83 vs 59 (gpt4)-30.8%
WinoGrande: 52.64 vs 87.5 (gpt4)-39.8%
GSM8K: 0.3 vs 96.4 (so35)-99.7%
LLME Score: 0.13303
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Opt 350M (facebook/opt-350m)
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Opt 350M Parameters and Internals

Model Type 
text generation, decoder-only model
Use Cases 
Areas:
Research, Text Generation
Primary Use Cases:
prompting for evaluation, text generation
Limitations:
bias, toxicity, generation diversity issues, hallucination
Considerations:
Fine-tuned models will inherit biases from the base model.
Supported Languages 
English (Predominantly)
Training Details 
Data Sources:
BookCorpus, CC-Stories, The Pile including subsets like Pile-CC, OpenWebText2, USPTO, Project Gutenberg, OpenSubtitles, Wikipedia, DM Mathematics, HackerNews, Pushshift.io Reddit, CCNewsV2
Data Volume:
180B tokens
Methodology:
Pretrained using a causal language modeling (CLM) objective
Context Length:
2048
Training Time:
~33 days
Hardware Used:
992 *80GB A100 GPUs
Model Architecture:
Causal language modeling
Safety Evaluation 
Risk Categories:
bias, toxicity, safety issues
Ethical Considerations:
The training data contains unfiltered content, which is not neutral leading to biased outputs.
Responsible Ai Considerations 
Transparency:
Data sources and limitations mentioned, but specifics of transparency not detailed.
Input Output 
Accepted Modalities:
text
Output Format:
Generated text
LLM NameOpt 350M
Repository 🤗https://huggingface.co/facebook/opt-350m 
Model Size350m
Required VRAM0.7 GB
Updated2025-07-31
Maintainerfacebook
Model Typeopt
Model Files  0.7 GB
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.20.0.dev0
Beginning of Sentence Token</s>
End of Sentence Token</s>
Unk Token</s>
Vocabulary Size50272
Torch Data Typefloat16
Activation Functionrelu
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than facebook/opt-350m.

Rank the Opt 350M 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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