Update README.md

README.md

@@ -12,8 +12,8 @@ tags:
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This is an official model checkpoint for Asclepius-Mixtral-8B-v0.3 [(arxiv)](https://arxiv.org/abs/2309.00237).
-This model is an enhanced version of Asclepius-7B, by replacing the base model with Mixtral-8B-v0.3 and increasing the max sequence length to 8192.
+This is an official model checkpoint for Asclepius-Mistral-7B-v0.3 [(arxiv)](https://arxiv.org/abs/2309.00237).
+This model is an enhanced version of Asclepius-7B, by replacing the base model with Mistral-7B-v0.3 and increasing the max sequence length to 8192.
 
 ## UPDATE
 ### 2024.01.10
@@ -30,7 +30,7 @@ This model is an enhanced version of Asclepius-7B, by replacing the base model w
 - **Model type:** Clinical LLM (Large Language Model)
 - **Language(s) (NLP):** English
 - **License:** CC-BY-NC-SA 4.0
-- **Finetuned from model [optional]:** Mixtral-8B-v0.3
+- **Finetuned from model [optional]:** Mistral-7B-v0.3
 
 ### Model Sources [optional]
 
@@ -89,8 +89,8 @@ The response should provide the accurate answer to the instruction, while being
 """
 
 from transformers import AutoTokenizer, AutoModelForCausalLM
-tokenizer = AutoTokenizer.from_pretrained("starmpcc/Asclepius-Mixtral-8B-v0.3", use_fast=False)
-model = AutoModelForCausalLM.from_pretrained("starmpcc/Asclepius-Mixtral-8B-v0.3")
+tokenizer = AutoTokenizer.from_pretrained("starmpcc/Asclepius-Mistral-7B-v0.3", use_fast=False)
+model = AutoModelForCausalLM.from_pretrained("starmpcc/Asclepius-Mistral-7B-v0.3")
 
 note = "This is a sample note"
 question = "What is the diagnosis?"