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README.md

@@ -11,12 +11,12 @@ inference: false
 ---
 
 <p align="center" width="100%">
-<img src="https://huggingface.co/bofenghuang/vigogne-30b-instruct/resolve/main/vigogne_logo.png" alt="Vigogne" style="width: 40%; min-width: 300px; display: block; margin: auto;">
+<img src="https://huggingface.co/bofenghuang/vigogne-33b-instruct/resolve/main/vigogne_logo.png" alt="Vigogne" style="width: 40%; min-width: 300px; display: block; margin: auto;">
 </p>
 
-# Vigogne-30B-Instruct: A French Instruction-following LLaMA Model
+# Vigogne-33B-Instruct: A French Instruction-following LLaMA Model
 
-Vigogne-30B-Instruct is a LLaMA-30B model fine-tuned to follow the French instructions.
+Vigogne-33B-Instruct is a LLaMA-33B model fine-tuned to follow the French instructions.
 
 For more information, please visit the Github repo: https://github.com/bofenghuang/vigogne
 
@@ -36,7 +36,7 @@ import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
 from vigogne.preprocess import generate_instruct_prompt
 
-model_name_or_path = "bofenghuang/vigogne-30b-instruct"
+model_name_or_path = "bofenghuang/vigogne-33b-instruct"
 tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, padding_side="right", use_fast=False)
 model = AutoModelForCausalLM.from_pretrained(model_name_or_path, torch_dtype=torch.float16, device_map="auto")