changed

README.md

@@ -34,7 +34,7 @@ widget:
 
 This repository contains a fine-tuned text-rewriting model based on the T5-Base with 223M parameters.
 
-Developed by: https://exnrt.com
+
 
 ## Key Features:
 
@@ -56,8 +56,8 @@ T5 model expects a task related prefix: since it is a paraphrasing task, we will
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 device = "cuda"
-tokenizer = AutoTokenizer.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='your_token')
-model = AutoModelForSeq2SeqLM.from_pretrained("Ateeqq/Text-Rewriter-Paraphraser", token='your_token').to(device)
+tokenizer = AutoTokenizer.from_pretrained("NoaiGPT/777", token='your_token')
+model = AutoModelForSeq2SeqLM.from_pretrained("NoaiGPT/777", token='your_token').to(device)
 
 def generate_title(text):
     input_ids = tokenizer(f'paraphraser: {text}', return_tensors="pt", padding="longest", truncation=True, max_length=64).input_ids.to(device)
@@ -85,12 +85,3 @@ generate_title(text)
  'Using transfer learning to use prior model training, fine-tuning can reduce the amount of expensive computing power and labeled data required for large models that are suitable in niche usage cases or businesses.']
 ```
 
-**Disclaimer:**
-
-* Limited Use: It grants a non-exclusive, non-transferable license to use the this model same as Llama-3. This means you can't freely share it with others or sell the model itself.
-* Commercial Use Allowed: You can use the model for commercial purposes, but under the terms of the license agreement.
-* Attribution Required: You need to abide by the agreement's terms regarding attribution. It is essential to use the paraphrased text responsibly and ethically, with proper attribution of the original source.
-
-**Further Development:**
-
-(Mention any ongoing development or areas for future improvement in Discussions.)