Update README.md

README.md

@@ -9,8 +9,7 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+
 
 # modelling
 
@@ -20,15 +19,16 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model generates hash tag from input text.  
 
 ## Intended uses & limitations
 
-More information needed
+
 
 ## Training and evaluation data
 
-More information needed
+This model was trained by the self-instruction process. 
+All data used for fine-tuning this model were generated by chatGPT 3.5.
 
 ## Training procedure
 
@@ -61,3 +61,20 @@ The following hyperparameters were used during training:
 - Pytorch 2.1.2+cu118
 - Datasets 2.16.1
 - Tokenizers 0.15.0
+
+
+### How to Get Started with the Model
+Use the code below to get started with the model.
+'''
+from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration
+model_name = "jjae/kobart-hashtag"
+tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+def make_tag(text):
+  input_ids = tokenizer.encode(text, return_tensors="pt").to(device)
+  output = model.generate(input_ids = input_ids, bos_token_id = model.config.bos_token_id,
+                          eos_token_id = model.config.eos_token_id, length_penalty = 2.0, max_length = 50, num_beams = 2)
+  decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
+  return decoded_output
+'''