Update README.md

README.md

@@ -3,7 +3,7 @@ license: apache-2.0
 language:
 - en
 base_model:
-- unsloth/Qwen2.5-72B-Instruct-bnb-4bit
+- unsloth/Qwen2.5-72B-Instruct
 pipeline_tag: text-generation
 library_name: transformers
 tags:
@@ -21,7 +21,7 @@ tags:
 This model, **Cogito-Maximus**, is a fine-tuned version of the `unsloth/qwen2.5-72b-instruct-bnb-4bit` base model, optimized for advanced text generation tasks. It leverages the power of **Unsloth** and **Huggingface's TRL (Transformer Reinforcement Learning)** library to achieve faster training and improved performance.
 
 ### **Key Features**
-- **Base Model:** `unsloth/qwen2.5-72b-instruct-bnb-4bit`
+- **Base Model:** `unsloth/qwen2.5-72b-instruct`
 - **Training Acceleration:** Trained 2x faster using [Unsloth](https://github.com/unslothai/unsloth).
 - **Fine-Tuning Framework:** Utilizes Huggingface's [TRL](https://github.com/huggingface/trl) library.
 - **Optimized for Inference:** Ready for deployment in text-generation tasks with efficient inference capabilities.
@@ -53,7 +53,7 @@ This model is released under the **Apache-2.0 License**, which allows for free u
 ## **Model Training**
 
 ### **Base Model**
-The model is derived from the `unsloth/qwen2.5-72b-instruct-bnb-4bit`, a quantized version of the Qwen2.5-72B instruction-tuned model. The base model is optimized for efficiency using **bitsandbytes (bnb)** 4-bit quantization.
+The model is derived from the `unsloth/qwen2.5-72b-instruct`, a  version of the Qwen2.5-72B instruction-tuned model. The base model is optimized for efficiency using **bitsandbytes (bnb)** 4-bit quantization.
 
 ### **Training Process**
 - **Framework:** The model was fine-tuned using **Unsloth**, a library designed to accelerate the training of large language models.