Update README.md

README.md

@@ -39,20 +39,23 @@ This model is a fine-tuned version of t5-small on a custom dataset derived from
 
 The Inference Api on the hugging face model page doesn't work well, load the model in jupyter notebook using the following code snippet:
   
-    text = "" # add your hieroglyph gardiner code combination in the string
     
+    text = "Translate hieroglyph gardiner code sequence to English: A4 A5 "
+
     from transformers import AutoTokenizer
     
-    tokenizer = AutoTokenizer.from_pretrained("AnushS/hieroglyph_unicode_translator_t5_small")
+    tokenizer = AutoTokenizer.from_pretrained("Hieroglyph-Translator-Using-Gardiner-Codes")
     inputs = tokenizer(text, return_tensors="pt").input_ids
     
     from transformers import AutoModelForSeq2SeqLM
     
-    
-    model = AutoModelForSeq2SeqLM.from_pretrained("AnushS/hieroglyph_unicode_translator_t5_small")
+    model = AutoModelForSeq2SeqLM.from_pretrained("Hieroglyph-Translator-Using-Gardiner-Codes")
     outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
     translated_keywords = str(tokenizer.decode(outputs[0], skip_special_tokens=True))
 
+    print(translated_keywords)
+
+print(translated_keywords)
 
 Intended uses & limitations
 
@@ -64,8 +67,8 @@ The Model is intended to be used to translate hieroglyphs. The model does not pr
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 1
-- eval_batch_size: 1
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear