Change toctree

notebooks/en/_toctree.yml

@@ -2,37 +2,47 @@
   sections:
   - local: index
     title: Open-Source AI Cookbook
-  - local: issues_in_text_dataset
-    title: Detecting Issues in a Text Dataset with Cleanlab
-  - local: stable_diffusion_interpolation
-    title: Stable Diffusion Interpolation
-  - local: rag_with_hugging_face_gemma_mongodb
-    title: Building A RAG System with Gemma, MongoDB and Open Source Models
-  - local: tgi_messages_api_demo
-    title: Migrating from OpenAI to Open LLMs Using TGI's Messages API
+
+- title: LLM Recipes
+  sections:
   - local: automatic_embedding_tei_inference_endpoints
     title: Automatic Embeddings with TEI through Inference Endpoints
-  - local: faiss_with_hf_datasets_and_clip
-    title: Embedding multimodal data for similarity search
+  - local: tgi_messages_api_demo
+    title: Migrating from OpenAI to Open LLMs Using TGI's Messages API
+  - local: advanced_rag
+    title: Advanced RAG on HuggingFace documentation using LangChain
+  - local: labelling_feedback_setfit
+    title: Suggestions for Data Annotation with SetFit in Zero-shot Text Classification
   - local: fine_tuning_code_llm_on_single_gpu
     title: Fine-tuning a Code LLM on Custom Code on a single GPU
+  - local: prompt_tuning_peft
+    title: Prompt tuning with PEFT
+  - local: rag_evaluation
+    title: RAG Evaluation
+  - local: llm_judge
+    title: Using LLM-as-a-judge for an automated and versatile evaluation
+
+- title: Diffusion Recipes
+  sections:
+  - local: stable_diffusion_interpolation
+    title: Stable Diffusion Interpolation
+
+- title: Multimodal Recipes
+  - local: faiss_with_hf_datasets_and_clip
+    title: Embedding multimodal data for similarity search
+
+- title: LLM and RAG recipes with other Libraries
+  - local: issues_in_text_dataset
+    title: Detecting Issues in a Text Dataset with Cleanlab
+  - local: annotate_text_data_transformers_via_active_learning
+    title: Annotate text data using Active Learning with Cleanlab
+  - local: rag_with_hugging_face_gemma_mongodb
+    title: Building A RAG System with Gemma, MongoDB and Open Source Models
   - local: rag_zephyr_langchain
     title: Simple RAG using Hugging Face Zephyr and LangChain
   - local: rag_llamaindex_librarian
     title: RAG "Librarian" Using LlamaIndex
-  - local: advanced_rag
-    title: Advanced RAG on HuggingFace documentation using LangChain
-  - local: rag_evaluation
-    title: RAG Evaluation
-  - local: prompt_tuning_peft
-    title: Prompt tuning with PEFT
-  - local: labelling_feedback_setfit
-    title: Suggestions for Data Annotation with SetFit in Zero-shot Text Classification
   - local: pipeline_notus_instructions_preferences_legal
     title: Create a legal preference dataset
   - local: semantic_cache_chroma_vector_database
     title: Implementing semantic cache to improve a RAG system.
-  - local: annotate_text_data_transformers_via_active_learning
-    title: Annotate text data using Active Learning with Cleanlab
-  - local: llm_judge
-    title: Using LLM-as-a-judge for an automated and versatile evaluation

notebooks/en/index.md

@@ -10,20 +10,6 @@ Check out the recently added notebooks:
 - [Using LLM-as-a-judge 🧑‍⚖️ for an automated and versatile evaluation](llm_judge)
 - [Create a legal preference dataset](pipeline_notus_instructions_preferences_legal)
 - [Suggestions for Data Annotation with SetFit in Zero-shot Text Classification](labelling_feedback_setfit)
-- [Implementing semantic cache to improve a RAG system](semantic_cache_chroma_vector_database)
-- [Building A RAG Ebook "Librarian" Using LlamaIndex](rag_llamaindex_librarian)
-- [Stable Diffusion Interpolation](stable_diffusion_interpolation)
-- [Building A RAG System with Gemma, MongoDB and Open Source Models](rag_with_hugging_face_gemma_mongodb)
-- [Prompt Tuning with PEFT Library](prompt_tuning_peft)
-- [Migrating from OpenAI to Open LLMs Using TGI's Messages API](tgi_messages_api_demo)
-- [Automatic Embeddings with TEI through Inference Endpoints](automatic_embedding_tei_inference_endpoints)
-- [Simple RAG for GitHub issues using Hugging Face Zephyr and LangChain](rag_zephyr_langchain)
-- [Embedding multimodal data for similarity search using 🤗 transformers, 🤗 datasets and FAISS](faiss_with_hf_datasets_and_clip)
-- [Fine-tuning a Code LLM on Custom Code on a single GPU](fine_tuning_code_llm_on_single_gpu)
-- [RAG Evaluation Using Synthetic data and LLM-As-A-Judge](rag_evaluation)
-- [Advanced RAG on HuggingFace documentation using LangChain](advanced_rag)
-- [Detecting Issues in a Text Dataset with Cleanlab](issues_in_text_dataset)
-- [Annotate text data using Active Learning with Cleanlab](annotate_text_data_transformers_via_active_learning)
 
 You can also check out the notebooks in the cookbook's [GitHub repo](https://github.com/huggingface/cookbook).