Update README.md

README.md

@@ -1,3 +1,46 @@
----
-license: cc-by-nc-sa-4.0
----
+---
+license: cc-by-nc-sa-4.0
+---
+# ProkBERT PhaStyle
+
+**Model Name**: neuralbioinfo/PhaStyle-mini   
+**Model Type**: Genomic Language Model (BERT-based)  
+**Model Description**:  
+
+ProkBERT PhaStyle is a fine-tuned genomic language model designed for phage lifestyle prediction. It classifies phages as either **virulent** or **temperate** directly from nucleotide sequences. The model is based on BERT architecture and was trained on the **BACPHLIP dataset**, excluding *E. coli* sequences, allowing it to generalize to phages beyond the *E. coli* domain.
+
+By leveraging transfer learning, ProkBERT PhaStyle is optimized for handling **fragmented sequences**, commonly encountered in metagenomic and metavirome datasets. The model provides a fast, efficient alternative to traditional methods without requiring complex preprocessing pipelines or curated databases.
+
+### Key Points:
+- **Trained on BACPHLIP** dataset excluding *E. coli* sequences.
+- **Segment Length** for training: 512 base pairs.
+- **Output**: Binary classification (virulent or temperate).
+- **Model Parameters**: ~21-26 million parameters depending on the variant used.
+
+---
+
+## Intended Use
+
+ProkBERT PhaStyle is designed for phage lifestyle prediction tasks, suitable for:
+
+- **Phage Therapy**: Identifying virulent phages for bacterial infection treatment.
+- **Microbiome Engineering**: Understanding the interaction between temperate and virulent phages in various microbiomes.
+- **Metagenomic Studies**: Classifying fragmented phage sequences from environmental or clinical samples.
+
+### Inference Code
+
+ProkBERT PhaStyle requires the **ProkBERT tokenizer** and a **custom classification model** (`BertForBinaryClassificationWithPooling`). Below is a high-level overview of how to use the model in inference mode:
+
+```python
+aaa
+```
+
+```bash
+python bin/PhaStyle.py \
+    --fastain data/EXTREMOPHILE/extremophiles.fasta \
+    --out output_predictions.tsv \
+    --ftmodel neuralbioinfo/PhaStyle-mini \
+    --modelclass BertForBinaryClassificationWithPooling \
+    --per_device_eval_batch_size 196
+
+```