Update README.md

README.md

@@ -9,6 +9,7 @@ tags:
 license: apache-2.0
 language:
 - en
+new_version: Daemontatox/PathFinderAI2.0
 ---
 
 # QWQ-32B Model Card
@@ -18,7 +19,7 @@ language:
 - **Base Model:** [unsloth/qwq-32b-preview-bnb-4bit](https://huggingface.co/unsloth/qwq-32b-preview-bnb-4bit)  
 
 ## Model Overview
-The QWQ-32B model is an advanced large language model (LLM) designed for high-performance text generation tasks. It has been finetuned from the base model using the [Unsloth](https://github.com/unslothai/unsloth) framework and Hugging Face's TRL library, achieving superior speed and efficiency during training. 
+The PathFinderAI2.0 is an advanced large language model (LLM) designed for high-performance text generation tasks. It has been finetuned from the base model using the [Unsloth](https://github.com/unslothai/unsloth) framework and Hugging Face's TRL library, achieving superior speed and efficiency during training. 
 
 ### Key Features
 - **Enhanced Training Speed:** Training was completed 2x faster compared to traditional methods, thanks to the optimization techniques provided by Unsloth.
@@ -32,7 +33,7 @@ The QWQ-32B model is an advanced large language model (LLM) designed for high-pe
 - Research Assistance
 
 ### Performance Metrics
-The QWQ-32B model demonstrates SOTA-level benchmarks across multiple text-generation datasets, highlighting its capabilities in both reasoning and creativity-focused tasks. Detailed evaluation results will be released in an upcoming report.
+The PathFinderAI2.0 model demonstrates High-level benchmarks across multiple text-generation datasets, highlighting its capabilities in both reasoning and creativity-focused tasks. Detailed evaluation results will be released in an upcoming report.
 
 ### Model Training
 The finetuning process leveraged:
@@ -49,8 +50,8 @@ You can load the model with Hugging Face's Transformers library:
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("Daemontatox/QWQ-32B")
-model = AutoModelForCausalLM.from_pretrained("Daemontatox/QWQ-32B", device_map="auto", load_in_4bit=True)
+tokenizer = AutoTokenizer.from_pretrained("Daemontatox/PathFinderAI2.0")
+model = AutoModelForCausalLM.from_pretrained("Daemontatox/PathFinderAI2.0", device_map="auto", load_in_4bit=True)
 
 inputs = tokenizer("Your input text here", return_tensors="pt")
 outputs = model.generate(**inputs)
@@ -58,6 +59,6 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```
 
 ### Acknowledgments
-Special thanks to the Unsloth team and the Hugging Face community for their support and tools, making the development of QWQ-32B possible.
+Special thanks to the Unsloth team and the Hugging Face community for their support and tools, making the development of PathFinderAI2.0 possible.
 
-[![Made with Unsloth](https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png)](https://github.com/unslothai/unsloth)
+[![Made with Unsloth](https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png)](https://github.com/unslothai/unsloth)