Update README.md

README.md

@@ -7,4 +7,37 @@ license: gpl-3.0
 
 This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
 - Library: [More Information Needed]
-- Docs: [More Information Needed]
+- Docs: [More Information Needed]
+
+## Steps to run model
+- First install [transforna](https://github.com/gitHBDX/TransfoRNA/tree/master)
+- Example code:
+```
+from transforna import GeneEmbeddModel,RnaTokenizer
+import torch
+model_name = 'Seq-Struct'
+model_path = f"HBDX/{model_name}-TransfoRNA"
+
+#load model and tokenizer
+model = GeneEmbeddModel.from_pretrained(model_path)
+model.eval()
+
+#init tokenizer. Tokenizer will automatically get secondary structure of sequence using Vienna RNA package
+tokenizer = RnaTokenizer.from_pretrained(model_path,model_name=model_name)
+output = tokenizer(['AAAGTCGGAGGTTCGAAGACGATCAGATAC','TTTTCGGAACTGAGGCCATGATTAAGAGGG'])
+
+#inference
+#gene_embedds and second input embedds are the latent space representation of the input sequence and the second input respectively.
+#In this case, the second input would be the secondary structure of the sequence
+gene_embedd, second_input_embedd, activations,attn_scores_first,attn_scores_second = \
+                                model(output['input_ids'])
+
+
+#get sub class labels
+sub_class_labels = model.convert_ids_to_labels(activations)
+
+#get major class labels
+major_class_labels = model.convert_subclass_to_majorclass(sub_class_labels)
+
+  ```
+