Add a tokenizer placeholder

modules/text_generation.py

@@ -21,8 +21,11 @@ def get_max_prompt_length(tokens):
     return max_length
 
 def encode(prompt, tokens_to_generate=0, add_special_tokens=True):
+
+    # These models do not have explicit tokenizers for now, so
+    # we return an estimate on the number of tokens
     if shared.is_RWKV or shared.is_LLaMA:
-        return prompt
+        return np.zeros((1, len(prompt)//5))
 
     input_ids = shared.tokenizer.encode(str(prompt), return_tensors='pt', truncation=True, max_length=get_max_prompt_length(tokens_to_generate), add_special_tokens=add_special_tokens)
     if shared.args.cpu: