nvidia
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quality-classifier-deberta

pytorch_model_hub_mixin

model_hub_mixin

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ryantwolf commited on Aug 6

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@@ -14,7 +14,7 @@ The model was trained using data annotated by human annotators, who considered q
 This model is used in the [NVIDIA NeMo Curator](https://github.com/NVIDIA/NeMo-Curator) as part of the qualitative filtering module.
 # Model Architecture
 The model architecture is Deberta V3 Base
-Context length is 512 tokens
 # Training (details)
 ## Training data:
 - 1 million Common Crawl samples, labeled using Google Cloud’s Natural Language API: https://cloud.google.com/natural-language/docs/classifying-text

 This model is used in the [NVIDIA NeMo Curator](https://github.com/NVIDIA/NeMo-Curator) as part of the qualitative filtering module.
 # Model Architecture
 The model architecture is Deberta V3 Base
+Context length is 1024 tokens
 # Training (details)
 ## Training data:
 - 1 million Common Crawl samples, labeled using Google Cloud’s Natural Language API: https://cloud.google.com/natural-language/docs/classifying-text