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README.md

@@ -2,6 +2,7 @@
 license: other
 ---
 [![License](https://img.shields.io/badge/license-GenBio_AI_Community_License-orange)](https://github.com/genbio-ai/ModelGenerator/blob/main/LICENSE)
+
 # How to use
 ```python
 from transformers import AutoModel, AutoTokenizer
@@ -16,6 +17,11 @@ model = AutoModel.from_pretrained(
     trust_remote_code=True,
     base_model="genbio-ai/AIDO.RNA-650M-CDS",
 )
+
+dna = "ACGTAGCATCGGATCTATCTATCGACACTTGGTTATCGATCTACGAGCATCTCGTTAGC"
+inputs = tokenizer(dna, add_special_tokens=True, return_tensors="pt")
+
+embedding = model(**inputs).last_hidden_state # [1, sequence_length, 1280]
 ```
 
 # Model Variants
@@ -70,12 +76,9 @@ model = AutoModel.from_pretrained(
 )
 
 dna = "ACGTAGCATCGGATCTATCTATCGACACTTGGTTATCGATCTACGAGCATCTCGTTAGC"
-inputs = tokenizer(dna, add_special_tokens=True, return_special_tokens_mask=True, return_tensors="pt")
+inputs = tokenizer(dna, add_special_tokens=True, return_tensors="pt")
 
-embedding = model(
-    input_ids=inputs["input_ids"],
-    attention_mask=inputs["attention_mask"],
-).last_hidden_state # [1, sequence_length, 1280]
+embedding = model(**inputs).last_hidden_state # [1, sequence_length, 1280]
 
 embedding_mean = torch.mean(embedding, dim=1)
 print(torch.mean(embedding_mean)) # Outputs tensor(0.0005, grad_fn=<MeanBackward0>)