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segment_nt

Feature Extraction

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hdallatorre commited on Mar 14

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@@ -40,7 +40,8 @@ Segment-NT-multi-species has been shown to generalize up to sequences of 50,000
 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
 (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`.
-🧬 The `./inference_segment_nt.ipynb` has been set up to run in Google Colab and shows how to set the rescaling factor and infer on a 50kb genic sequence of the human chromosome 20.
 ```python
 # Load model and tokenizer

 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
 (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`.
+[![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https%3A//huggingface.co/InstaDeepAI/segment_nt/blob/main/inference_segment_nt.ipynb)
+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.
 ```python
 # Load model and tokenizer