Update README.md

README.md

@@ -1,31 +1,40 @@
----
-license: mit
-task_categories:
-  - text-generation
-tags:
-  - biology
-  - genomics
-  - long-context
----
-
-## How to use
-
-```python
-from datasets import load_dataset
-
-datasets = load_dataset("GenerTeam/next_kmer_prediction")
-```
-
-## Citation
-
-```bibtex
-@misc{wu2025generator,
-    title={GENERator: A Long-Context Generative Genomic Foundation Model},
-    author={Wei Wu and Qiuyi Li and Mingyang Li and Kun Fu and Fuli Feng and Jieping Ye and Hui Xiong and Zheng Wang},
-    year={2025},
-    eprint={2502.07272},
-    archivePrefix={arXiv},
-    primaryClass={cs.CL},
-    url={https://arxiv.org/abs/2502.07272},
-}
-```
+---
+license: mit
+task_categories:
+  - text-generation
+tags:
+  - biology
+  - genomics
+  - long-context
+---
+
+# Next K-mer Prediction
+
+## Abouts
+The Next K-mer Prediction task is a zero-shot evaluation method introduced in the **GENERator** paper to assess the quality of pretrained models. It involves inputting a sequence segment into the model and having it predict the next K base pairs. The predicted sequence is then compared to the actual sequence to assess accuracy.
+* **Sequence**: The input sequence has a maximum length of 96k base pairs (bp). You can control the number of input tokens by applying **left** truncation.  
+* **Label**: The next 128 bp immediately following the end of the input sequence.  
+
+Note: Prediction time may increase significantly for longer input sequences. It is strongly recommended to begin testing with a smaller number of input tokens to optimize performance.  
+
+## How to use
+
+```python
+from datasets import load_dataset
+
+datasets = load_dataset("GenerTeam/next_kmer_prediction")
+```
+
+## Citation
+
+```bibtex
+@misc{wu2025generator,
+    title={GENERator: A Long-Context Generative Genomic Foundation Model},
+    author={Wei Wu and Qiuyi Li and Mingyang Li and Kun Fu and Fuli Feng and Jieping Ye and Hui Xiong and Zheng Wang},
+    year={2025},
+    eprint={2502.07272},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL},
+    url={https://arxiv.org/abs/2502.07272},
+}
+```