Pythia 6.9B Deduped 8K by openaccess-ai-collective

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  Arxiv:2101.00027   Arxiv:2201.07311   Autotrain compatible Dataset:eleutherai/the pile de...   En   Endpoints compatible   Ext 8k   Gpt neox   Pythia   Pytorch   Region:us   Sharded

Pythia 6.9B Deduped 8K Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Pythia 6.9B Deduped 8K Parameters and Internals

Model Type 
Transformer-based Language Model
Use Cases 
Areas:
Research
Primary Use Cases:
Research on behavior, functionality, and limitations of large language models.
Limitations:
Not intended for human-facing interactions; may generate harmful or offensive text., Only suitable for English language; not meant for translation or multilingual text generation.
Additional Notes 
Pythia models were retrained to address hyperparameter discrepancies; old versions are still available but the retrained suite is recommended.
Supported Languages 
English (high)
Training Details 
Data Sources:
The Pile
Data Volume:
299,892,736,000 tokens
Methodology:
Global deduplication was applied to the dataset.
Context Length:
8000
Training Time:
143000 steps
Model Architecture:
Transformer-based
Release Notes 
Version:
Current Release
Date:
January 2023
Notes:
Renamed models, uniform batch size, additional checkpoints, Flash Attention used, remedied learning rate schedule inconsistency.
LLM NamePythia 6.9B Deduped 8K
Repository ๐Ÿค—https://huggingface.co/openaccess-ai-collective/pythia-6.9b-deduped-8k 
Model Size6.9b
Required VRAM13.8 GB
Updated2025-06-09
Maintaineropenaccess-ai-collective
Model Typegpt_neox
Model Files  10.0 GB: 1-of-2   3.8 GB: 2-of-2
Supported Languagesen
Context Length8k
Model ArchitectureGPTNeoXForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.30.0.dev0
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50304
Torch Data Typebfloat16
Pythia 6.9B Deduped 8K (openaccess-ai-collective/pythia-6.9b-deduped-8k)

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Note: green Score (e.g. "73.2") means that the model is better than openaccess-ai-collective/pythia-6.9b-deduped-8k.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124