Update README.md

README.md

@@ -18,11 +18,11 @@ tokenizer = AutoTokenizer.from_pretrained("segestic/Tinystories-gpt-0.1-3m")
 model = AutoModelForCausalLM.from_pretrained("segestic/Tinystories-gpt-0.1-3m")
 prompt = "Once upon a time there was"
 input_ids = tokenizer.encode(prompt, return_tensors="pt")
-### Generate completion
+#### Generate completion
 output = model.generate(input_ids, max_length = 1000, num_beams=1)
-### Decode the completion
+#### Decode the completion
 output_text = tokenizer.decode(output[0], skip_special_tokens=True)
-### Print the generated text
+#### Print the generated text
 print(output_text)
 
 
@@ -30,11 +30,14 @@ print(output_text)
 # ------ EXAMPLE USAGE 2 ------
 ## Use a pipeline as a high-level helper
 from transformers import pipeline
-
+#### pipeline
 pipe = pipeline("text-generation", model="segestic/Tinystories-gpt-0.1-3m")
+#### prompt
 prompt = "where is the little girl"
+#### generate completion
 output = pipe(prompt, max_length=1000, num_beams=1)
+#### decode the completion
 generated_text = output[0]['generated_text']
-### Print the generated text
+#### Print the generated text
 print(generated_text)