InstaDeepAI
/

segment_nt

Feature Extraction

Model card Files Files and versions Community

hdallatorre commited on Mar 14, 2024

Commit

f2513dc

·

verified ·

1 Parent(s): 3baab28

Update README.md

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -39,8 +39,8 @@ 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`.
-[![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)]
-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
 paper.
 ```python

 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)
+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
 paper.
 ```python