Update README.md

README.md

@@ -5,12 +5,12 @@ language:
 - en
 ---
 
-# Model Card for M4-ai/hyperion-small-preview
+# Model Card for Locutusque/hyperion-small-preview
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6437292ecd93f4c9a34b0d47/1lL97kzuxqykXGUT6F593.png)
 
 ## Model Details
-**Model Name**: M4-ai/hyperion-small-preview  
+**Model Name**: Locutusque/hyperion-small-preview  
 **Base Model**: Qwen/Qwen1.5-1.8B  
 **Publisher**: M4-ai
 **Model Type**: Question answering, conversational AI, code generation, medical text comprehension, mathematical reasoning, logical reasoning.  
@@ -18,7 +18,7 @@ language:
 **License**: Apache-2.0  
 
 ## Model Description
-`M4-ai/hyperion-small-preview` is a state-of-the-art language model fine-tuned on the Hyperion dataset for advanced reasoning across scientific domains. This model is designed to handle complex inquiries and instructions, leveraging the diverse and rich information contained in the Hyperion dataset. Its primary use cases include but are not limited to complex question answering, conversational understanding, code generation, medical text comprehension, mathematical reasoning, and logical reasoning. 
+`Locutusque/hyperion-small-preview` is a state-of-the-art language model fine-tuned on the Hyperion dataset for advanced reasoning across scientific domains. This model is designed to handle complex inquiries and instructions, leveraging the diverse and rich information contained in the Hyperion dataset. Its primary use cases include but are not limited to complex question answering, conversational understanding, code generation, medical text comprehension, mathematical reasoning, and logical reasoning. 
 
 ## Intended Use
 This model is intended for researchers and practitioners looking for a powerful tool to tackle challenging problems in scientific domains. It can be used in the following scenarios:
@@ -28,7 +28,7 @@ This model is intended for researchers and practitioners looking for a powerful
 - Automation in code generation and understanding complex programming context.
 
 ## Training Data
-The `M4-ai/hyperion-small-preview` model was fine-tuned on the Hyperion dataset, which amalgamates various datasets rich in diversity and complexity, including programming, medical texts, mathematical problems, and reasoning tasks.
+The `Locutusque/hyperion-small-preview` model was fine-tuned on the Hyperion dataset, which amalgamates various datasets rich in diversity and complexity, including programming, medical texts, mathematical problems, and reasoning tasks.
 
 ## Evaluation Results
 Coming soon...
@@ -37,7 +37,7 @@ Coming soon...
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "M4-ai/hyperion-small-preview"
+model_name = "Locutusque/hyperion-small-preview"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
@@ -57,7 +57,7 @@ The diversity of the dataset could lead to inconsistencies in the model's respon
 This model is released under the Apache-2.0 license.
 ## Citation Information
 
-If you use M4-ai/hyperion-small-preview in your research, please cite the Hyperion dataset as follows:
+If you use Locutusque/hyperion-small-preview in your research, please cite the Hyperion dataset as follows:
 
 ```
 @misc{sebastian_gabarain_2024,