Update README.md

7_inference/README.md

@@ -16,7 +16,7 @@ Learn how to use the Hugging Face Transformers pipeline for basic inference. We'
 
 ### 2. [Production Inference with TGI](./tgi_inference.md)
 
-Learn how to deploy models for production using Text Generation Inference. We'll explore optimized serving techniques, batching strategies, and monitoring solutions. TGI provides production-ready features like health checks, metrics, and Docker deployment options. [Start learning](./tgi_inference.md).
+Learn how to deploy models for production using Text Generation Inference. We'll explore optimized serving techniques, batching strategies, and monitoring solutions. TGI provides production-ready features like health checks, metrics, and Docker deployment options. [Start learning](./text_generation_inference.md).
 
 ### Exercise Notebooks
 
@@ -33,4 +33,4 @@ Learn how to deploy models for production using Text Generation Inference. We'll
 - [TGI GitHub Repository](https://github.com/huggingface/text-generation-inference)
 - [Hugging Face Model Deployment Documentation](https://huggingface.co/docs/inference-endpoints/index)
 - [vLLM: High-throughput LLM Serving](https://github.com/vllm-project/vllm)
-- [Optimizing Transformer Inference](https://huggingface.co/blog/optimize-transformer-inference)
+- [Optimizing Transformer Inference](https://huggingface.co/blog/optimize-transformer-inference)