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SOTA
Language Modelling
Language Modelling On The Pile
Language Modelling On The Pile
Metrics
Bits per byte
Results
Performance results of various models on this benchmark
Columns
Model Name
Bits per byte
Paper Title
GPT-2 Small 124M (pre-trained)
1.2253
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
GPT-2 Medium 355M (pre-trained)
1.0928
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
GPT-2 Large 774M (pre-trained)
1.0828
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
GPT-2 XL 1.5B (pre-trained)
1.0468
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
GPT-3 Ada 350M (pre-trained)
0.9631
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
GPT-3 Babbage 1.3B (pre-trained)
0.8718
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Test-Time Fine-Tuning with SIFT + GPT-2 (124M)
0.862
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
GPT-2 Large 774M (test-time training on nearest neighbors)
0.85
Test-Time Training on Nearest Neighbors for Large Language Models
Llama-3.2-Instruct 1B
0.807
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
GPT-3 Curie 6.7B (pre-trained)
0.7980
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Test-Time Fine-Tuning with SIFT + GPT-2 (774M)
0.762
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
GPT-3
0.742
GLM-130B: An Open Bilingual Pre-trained Model
Llama-3.2-Instruct 3B
0.737
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Gemma-2 2B
0.721
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
GPT-3 Davinci 175B (pre-trained)
0.7177
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Llama-3.2 1B
0.697
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Phi-3 3.8B
0.679
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Phi-3 7B
0.678
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Gemma-2 9B
0.670
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
Phi-3 14B
0.651
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs
0 of 39 row(s) selected.
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Language Modelling On The Pile | SOTA | HyperAI