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@@ -40,8 +40,7 @@ the `rescaling_factor` of the Rotary Embedding layer in the esm model `num_dna_
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  (i.e 6669 for a sequence of 40008 base pairs) and `max_num_tokens_nt` is the max number of tokens on which the backbone nucleotide-transformer was trained on, i.e `2048`.
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  ![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)
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- The `./inference_segment_nt.ipynb` notebook shows how to set the rescaling factor and infer on a 50kb sequence of the human chromosome 20 in order to reproduce Fig.3 of the
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- paper.
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  ```python
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  # Load model and tokenizer
 
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  (i.e 6669 for a sequence of 40008 base pairs) and `max_num_tokens_nt` is the max number of tokens on which the backbone nucleotide-transformer was trained on, i.e `2048`.
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  ![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)
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+ The `./inference_segment_nt.ipynb` notebook shows how to set the rescaling factor and infer on a 50kb genic sequence of the human chromosome 20.
 
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  ```python
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  # Load model and tokenizer