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                           <h3 class="ds-work-tilte">Fine-Tuning and Hosting Mistral-7B using TGI</a></h3>
-                          <p>Fine-Tuned a 7billion parameter model using huggingface on a 24GB VRAM A10g. The process involved creation of synthetic dataset using GPT4 APIs, which was cleaned before undergoing Parameter-Efficient Fine-Tuning (PEFT) on our systems. This process leveraged advanced quantization methods provided by quantization techinques from <a href="https://huggingface.co/blog/4bit-transformers-bitsandbytes"> bits and bytes </a> and <a href="https://mlabonne.github.io/blog/posts/A_Beginners_Guide_to_LLM_Finetuning.html">Axotol</a>.
+                          <p>Fine-Tuned a 7billion parameter model using huggingface on a 24GB VRAM A10g. The process involved creation of synthetic dataset using GPT4 APIs, which was cleaned before undergoing Parameter-Efficient Fine-Tuning (PEFT) on our systems. This process leveraged advanced quantization methods provided from <a href="https://huggingface.co/blog/4bit-transformers-bitsandbytes"> bits and bytes </a> and <a href="https://mlabonne.github.io/blog/posts/A_Beginners_Guide_to_LLM_Finetuning.html">Axotol</a>.
                               <br>The Model will be hosted using <a href = "https://huggingface.co/docs/text-generation-inference/en/index"> TGI </a>framework by huggingface.
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