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+ | Model Name | Parameters | Class | Ratio | Tokens | Batch Size (Tokens) | Training Loss ↓ |
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+ | --- | --- | --- | --- | --- | --- | --- |
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+ | [GerbilLab/GerbilBlender-A-32m](https://hf.co/GerbilLab/GerbilBlender-A-32m) | 32m | A-Class | 20 | 640M | 262K | 4.127 |
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+ "Blender" models, inspired by UL2 pretraining, are trained equally in fill-in-the-middle, causal modelling, and masked language modelling tasks. Special tokens for these models include:
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+ ```
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+ '<fitm_start>', '<multiple_tok_mask>', '<fitm_result>', '<causal>', '<mlm_start>', '<single_tok_mask>', '<mlm_end>'
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+ # Example fill in the middle
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+ '<fitm_start> this is an <multiple_tok_mask> for fill-in-the-middle <fitm_result> example text <|endoftext|>'
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+ # Example causal language modelling
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+ '<causal> this is an example text for causal language modelling <|endoftext|>'
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+ # Example masked language modelling
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+ '<mlm_start> this is an <single_tok_mask> text for masked language modelling <mlm_end> example <|endoftext|>'
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+ ```