Update README.md

README.md

@@ -1,18 +1,22 @@
 # Cheapity3 🐷
-"GPT-like" T5 model trained to generate text in multiple languages.
+
+GPT3-like T5 model trained to generate text in multiple languages.
 
 ## Motivation
+
 - GPT models are expensive run.
 - GPT models are monolingual.
 
 ## Solution
-- Maybe, Small Models aren't Terrible (*SMarT*) 
+
+- Maybe, Small Models aren't Terrible (*SMarT*)
 - Plus, they are cheaper to run.
 
-I fine-tuned T5 on multiple languages (🇬🇧 English, 🇩🇪 German, 🇫🇷 French) and multiple academic text snippets from various 
-domains like tech, law, finance and science etc. to generate text, just like GPT models do.
+I fine-tuned T5 on multiple languages (🇬🇧 English, 🇩🇪 German, 🇫🇷 French) and multiple academic text snippets from
+various domains like tech, law, finance and science etc. to generate text, just like GPT models do.
 
 ## Usage
+
 - Provide some text e.g `"Italy, officially the Italian Republic is a country consisting of"`
 - Tell Cheapity3 how many words you want to generate e.g `15` -- 😃 Yes, you can control the length.
 - Cheapity3 reads your text and generates a continuation containing approximately 15 words.
@@ -24,31 +28,33 @@ tokenizer = AutoTokenizer.from_pretrained("flexudy/cheapity3")
 
 model = AutoModelWithLMHead.from_pretrained("flexudy/cheapity3")
 
-input_text = "guess: Italy, officially the Italian Republic is a country consisting of { _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ }" # 15 words
+input_text = """The mechanical engineering field requires an understanding of core areas including mechanics, dynamics,
+ thermodynamics, materials science, structural analysis, and 
+ electricity. { _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ }"""  # 15 words
 
-inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True, max_length=512)
+inputs = tokenizer(input_text, return_tensors="pt", truncation=True, max_length=512)
 
 input_ids = inputs["input_ids"]
 
 attention_mask = inputs["attention_mask"]
 
 outputs = model.generate(
-            input_ids=input_ids,
-            attention_mask=attention_mask,
-            max_length=128,
-            do_sample=True,
-            early_stopping=True,
-            num_return_sequences=4,
-            repetition_penalty=2.5
-        )
+    input_ids=input_ids,
+    attention_mask=attention_mask,
+    max_length=128,
+    do_sample=True,
+    early_stopping=True,
+    num_return_sequences=4,
+    repetition_penalty=2.5
+)
 
 for i in range(4):
     print(tokenizer.decode(outputs[i], skip_special_tokens=True, clean_up_tokenization_spaces=True))
 
-# > 
-# > 
-# > 
-# > 
-```
-
-# 
+# Italy, officially the Italian Republic is a country consisting of 
+# > Cheapity3 continuing:
+# ... Developing the knowledge base for these core areas will enable engineers to build their capabilities rapidly and efficiently. ...
+# ... The field of mechanics offers a variety and broad range for applications throughout the engineering/technological fields. ...
+# ... Mechanics generally is not understood by students. While they can be employed in the field, mechanical engineering ...
+# ... Introduction to mechanical engineering and core fields including chemical products, materials science, structural analysis, and geomatics ...
+```