fix: typos

README.md

@@ -4,15 +4,15 @@ tags:
 - human_genome
 ---
 
-# GENA-LM (gena-lm-bigbird-base-sparse-t2t-t2t)
+# GENA-LM (gena-lm-bigbird-base-sparse-t2t)
 
 GENA-LM is a Family of Open-Source Foundational Models for Long DNA Sequences.
 
 GENA-LM models are transformer masked language models trained on human DNA sequence. 
 
-`gena-lm-bigbird-base-sparse-t2t-t2t` follows the BigBird architecture and uses sparse attention from DeepSpeed.
+`gena-lm-bigbird-base-sparse-t2t` follows the BigBird architecture and uses sparse attention from DeepSpeed.
 
-Differences between GENA-LM (`gena-lm-bigbird-base-sparse-t2t-t2t`) and DNABERT:
+Differences between GENA-LM (`gena-lm-bigbird-base-sparse-t2t`) and DNABERT:
 - BPE tokenization instead of k-mers;
 - input sequence size is about 36000 nucleotides (4096 BPE tokens) compared to 512 nucleotides of DNABERT;
 - pre-training on T2T vs. GRCh38.p13 human genome assembly.
@@ -22,7 +22,7 @@ Source code and data: https://github.com/AIRI-Institute/GENA_LM
 Paper: https://www.biorxiv.org/content/10.1101/2023.06.12.544594v1
 
 ## Installation
-`gena-lm-bigbird-base-sparse-t2t-t2t` sparse ops require DeepSpeed.
+`gena-lm-bigbird-base-sparse-t2t` sparse ops require DeepSpeed.
 
 ### DeepSpeed
 DeepSpeed installation is needed to work with SparseAttention versions of language models. DeepSpeed Sparse attention supports only GPUs with compute compatibility >= 7 (V100, T4, A100).