Update README.md

README.md

@@ -14,11 +14,10 @@ tags:
 pipeline_tag: text-generation
 ---
 
-# Model Card: Engine_Finetuned_V2.2
 
 ## Model Details
 
-**Model Name:** Engine_Finetuned_V2.2  
+**Model Name:** UMA-IA/LLM_Engine_Finetuned_Aero 
 **Authors:**  
 - **Youri LALAIN**, Engineering student at French Engineering School ECE  
 - **Lilian RAGE**, Engineering student at French Engineering School ECE  
@@ -31,7 +30,7 @@ pipeline_tag: text-generation
 
 # Mistral-7B Fine-tuné sur les moteurs aérospatiaux
 
-Engine_Finetuned_V2.2 is a specialized fine-tuned version of Mistral-7B designed to provide accurate and detailed answers to technical questions related to aerospace and aeronautical engines. The model leverages the SpaceYL/Aerospatial_Dataset to enhance its understanding of complex engineering principles, propulsion systems, and aerospace technologies.
+LLM_Engine_Finetuned_Aero is a specialized fine-tuned version of Mistral-7B designed to provide accurate and detailed answers to technical questions related to aerospace and aeronautical engines. The model leverages the SpaceYL/Aerospatial_Dataset to enhance its understanding of complex engineering principles, propulsion systems, and aerospace technologies.
 
 ## Capabilities
 - Technical Q&A on aerospace and aeronautical engines
@@ -44,7 +43,7 @@ Engine_Finetuned_V2.2 is a specialized fine-tuned version of Mistral-7B designed
 - Assisting in aerospace-related R&D projects
 
 ## Training Details
-This model was fine-tuned on SpaceYL/Aerospatial_Dataset, a curated dataset focusing on aerospace engines, propulsion systems, and general aeronautical engineering. The fine-tuning process was performed using supervised learning to adapt Mistral-7B to technical discussions.
+This model was fine-tuned on UMA-IA/UMA_Dataset_Engine_Aero_LLM, a curated dataset focusing on aerospace engines, propulsion systems, and general aeronautical engineering. The fine-tuning process was performed using supervised learning to adapt Mistral-7B to technical discussions.
 
 
 ## How to Use
@@ -53,7 +52,7 @@ You can load the model using Hugging Face's `transformers` library:
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "SpaceYL/Engine_Finetuned_V2.2"
+model_name = "UMA-IA/LLM_Engine_Finetuned_Aero"
 
 model = AutoModelForCausalLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)