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README.md
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@@ -40,7 +40,8 @@ Segment-NT-multi-species has been shown to generalize up to sequences of 50,000
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the `rescaling_factor` of the Rotary Embedding layer in the esm model `num_dna_tokens_inference / max_num_tokens_nt` where `num_dna_tokens_inference` is the number of tokens at inference
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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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```python
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# Load model and tokenizer
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the `rescaling_factor` of the Rotary Embedding layer in the esm model `num_dna_tokens_inference / max_num_tokens_nt` where `num_dna_tokens_inference` is the number of tokens at inference
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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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[](https://colab.research.google.com/#fileId=https%3A//huggingface.co/InstaDeepAI/segment_nt/blob/main/inference_segment_nt.ipynb)
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The `./inference_segment_nt.ipynb` can be run in Google Colab by clicking on the icon and 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
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