Update README.md

README.md

@@ -9,8 +9,6 @@ tags:
 
 # Aegolius Acadicus 24B V2
 
-# Aegolius Acadicus 30B
-
 ![img](./aegolius-acadicus.png)
 
 I like to call this model "The little professor".  It is simply a MOE merge of lora merged models across Llama2 and Mistral.  I am using this as a test case to move to larger models and get my gate discrimination set correctly.  This model is best suited for knowledge related use cases, I did not give it a specific workload target as I did with some of the other models in the "Owl Series".
@@ -48,8 +46,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 
 torch.set_default_device("cuda")
 
-model = AutoModelForCausalLM.from_pretrained("ibivibiv/aegolius-acadicus-30b", torch_dtype="auto", device_config='auto')
-tokenizer = AutoTokenizer.from_pretrained("ibivibiv/aegolius-acadicus-30b")
+model = AutoModelForCausalLM.from_pretrained("ibivibiv/aegolius-acadicus-24b-v2", torch_dtype="auto", device_config='auto')
+tokenizer = AutoTokenizer.from_pretrained("ibivibiv/aegolius-acadicus-24b-v2")
 
 inputs = tokenizer("### Instruction: Who would when in an arm wrestling match between Abraham Lincoln and Chuck Norris?\n### Response:\n", return_tensors="pt", return_attention_mask=False)