remove fallback to transformer section

Author: baptistecolle

intel-gaudi-backend-for-tgi.md

@@ -70,10 +70,8 @@ We have optimized the following models for both single and multi-card configurat
 - Gemma (7B) 
 - Llava-v1.6-Mistral-7B 
 
-Furthermore, we also support all models implemented in the [Transformers library](https://huggingface.co/docs/transformers/index), providing a [fallback mechanism](https://huggingface.co/docs/text-generation-inference/basic_tutorials/non_core_models) that ensures you can still run any model on Gaudi hardware even if it's not yet specifically optimized.
-
 🏃‍♂️ We also offer many advanced features on Gaudi hardware, such as FP8 quantization thanks to [Intel Neural Compressor (INC)](https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Quantization/Inference_Using_FP8.html), enabling even greater performance optimizations.
 
 ## 💪 Getting Involved 
 
-We invite the community to try out TGI on Gaudi hardware and provide feedback. The full documentation is available in the [TGI Gaudi backend documentation](https://huggingface.co/docs/text-generation-inference/backends/gaudi). 📚 If you're interested in contributing, check out our contribution guidelines or open an issue with your feedback on GitHub. 🤝 By bringing Intel Gaudi support directly into TGI, we're continuing our mission to provide flexible, efficient, and production-ready tools for deploying LLMs. We're excited to see what you'll build with this new capability! 🎉
+We invite the community to try out TGI on Gaudi hardware and provide feedback. The full documentation is available in the [TGI Gaudi backend documentation](https://huggingface.co/docs/text-generation-inference/backends/gaudi). 📚 If you're interested in contributing, check out our contribution guidelines or open an issue with your feedback on GitHub. 🤝 By bringing Intel Gaudi support directly into TGI, we're continuing our mission to provide flexible, efficient, and production-ready tools for deploying LLMs. We're excited to see what you'll build with this new capability! 🎉