Force use of the slow tokenizer to avoid tokenizer.json issues

README.md

@@ -40,16 +40,14 @@ Run model in Python:
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("SVECTOR-CORPORATION/Theta-35-Mini")
+# Force use of the slow tokenizer to avoid tokenizer.json issues
+tokenizer = AutoTokenizer.from_pretrained("SVECTOR-CORPORATION/Theta-35-Mini", use_fast=False)
 model = AutoModelForCausalLM.from_pretrained("SVECTOR-CORPORATION/Theta-35-Mini")
 
-# Prompt input
 inputs = tokenizer("Once upon a time", return_tensors="pt")
 
-# Generate output
 outputs = model.generate(**inputs, max_length=100, temperature=0.7)
 
-# Decode and print
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```