- title: Open-Source AI Cookbook isExpanded: True sections: - local: index title: Overview - title: MLOps Recipes isExpanded: false sections: - local: mlflow_ray_serve title: Signature-Aware Model Serving from MLflow with Ray Serve - title: LLM Recipes isExpanded: false sections: - local: automatic_embedding_tei_inference_endpoints title: Automatic Embeddings with TEI through Inference Endpoints - 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_with_hf_and_milvus title: RAG with Hugging Face and Milvus - local: rag_evaluation title: RAG Evaluation - local: llm_judge title: Using LLM-as-a-judge for an automated and versatile evaluation - local: llm_judge_evaluating_ai_search_engines_with_judges_library title: Evaluating AI Search Engines with `judges` - the open-source library for LLM-as-a-judge evaluators - 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_elasticsearch title: Building a RAG System with Gemma, Elasticsearch and Open Source Models - 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: semantic_cache_chroma_vector_database title: Implementing semantic cache to improve a RAG system. - local: structured_generation title: RAG with source highlighting using Structured generation - local: rag_with_unstructured_data title: Building RAG with Custom Unstructured Data - local: fine_tuning_llm_to_generate_persian_product_catalogs_in_json_format title: Fine-tuning LLM to Generate Persian Product Catalogs in JSON Format - local: finetune_t5_for_search_tag_generation title: Fine-tuning T5 for Automatic GitHub Tag Generation with PEFT - local: llm_gateway_pii_detection title: LLM Gateway for PII Detection - local: information_extraction_haystack_nuextract title: Information Extraction with Haystack and NuExtract - local: code_search title: Code Search With Vector Embeddings Using Qdrant - local: rag_with_sql_reranker title: RAG backed by SQL and Jina Reranker - local: generate_preference_dataset_distilabel title: Generate a Preference Dataset with distilabel - local: clean_dataset_judges_distilabel title: Clean an Existing Preference Dataset with LLMs as Judges - local: benchmarking_tgi title: Benchmarking TGI - local: rag_with_knowledge_graphs_neo4j title: Enhancing RAG Reasoning with Knowledge Graphs - local: phoenix_observability_on_hf_spaces title: Phoenix Observability Dashboard on HF Spaces - local: search_and_learn title: Scaling Test-Time Compute for Longer Thinking in LLMs - local: fine_tuning_llm_grpo_trl title: Post training an LLM for reasoning with GRPO in TRL - local: trl_grpo_reasoning_advanced_reward title: TRL GRPO Reasoning with Advanced Reward - local: medical_rag_and_reasoning title: HuatuoGPT-o1 Medical RAG and Reasoning - local: fine_tune_chatbot_docs_synthetic title: Documentation Chatbot with Meta Synthetic Data Kit - local: optuna_hpo_with_transformers title: Hyperparameter Optimization with Optuna and Transformers - local: function_calling_fine_tuning_llms_on_xlam title: Fine-tuning LLMs for Function Calling with the xLAM Dataset - local: dspy_gepa title: Optimizing Language Models with DSPy GEPA - local: grpo_vllm_online_training title: Efficient Online Training with GRPO and vLLM in TRL - local: rapidfire_sft_multiconfig_training title: Concurrent Multi-Config SFT Training with RapidFire AI - title: Computer Vision Recipes isExpanded: false sections: - local: fine_tuning_vit_custom_dataset title: Fine-tuning a Vision Transformer Model With a Custom Biomedical Dataset - local: fine_tuning_detr_custom_dataset title: Fine-Tuning Object Detection on a Custom Dataset, Deployment in Spaces, and Gradio API Integration - local: semantic_segmentation_fine_tuning_inference title: Fine-Tuning a Semantic Segmentation Model on a Custom Dataset and Usage via the Inference API - title: Diffusion Recipes isExpanded: false sections: - local: stable_diffusion_interpolation title: Stable Diffusion Interpolation - title: Multimodal Recipes isExpanded: false sections: - local: analyzing_art_with_hf_and_fiftyone title: Analyzing Artistic Styles with Multimodal Embeddings - local: faiss_with_hf_datasets_and_clip title: Embedding multimodal data for similarity search - local: multimodal_rag_using_document_retrieval_and_vlms title: Multimodal Retrieval-Augmented Generation (RAG) with Document Retrieval (ColPali) and Vision Language Models (VLMs) - local: fine_tuning_vlm_trl title: Fine-Tuning a Vision Language Model (Qwen2-VL-7B) with the Hugging Face Ecosystem (TRL) - local: multimodal_rag_using_document_retrieval_and_reranker_and_vlms title: Multimodal RAG with ColQwen2, Reranker, and Quantized VLMs on Consumer GPUs - local: fine_tuning_smol_vlm_sft_trl title: Fine-tuning SmolVLM with TRL on a consumer GPU - local: multimodal_rag_using_document_retrieval_and_smol_vlm title: Smol Multimodal RAG, Building with ColSmolVLM and SmolVLM on Colab's Free-Tier GPU - local: fine_tuning_vlm_dpo_smolvlm_instruct title: Fine-tuning SmolVLM using direct preference optimization (DPO) with TRL on a consumer GPU - local: structured_generation_vision_language_models title: Structured Generation from Images or Documents Using Vision Language Models - local: fine_tuning_granite_vision_sft_trl title: Fine-tuning Granite Vision with TRL - local: fine_tuning_vlm_object_detection_grounding title: Fine tuning a VLM for Object Detection Grounding using TRL - local: fine_tuning_vlm_mpo title: Fine-Tuning a Vision Language Model with TRL using MPO - local: fine_tuning_vlm_grpo_trl title: Post training an VLM for reasoning with GRPO using TRL - title: Search Recipes isExpanded: false sections: - local: semantic_reranking_elasticsearch title: Semantic Reranking with Elasticsearch - local: vector_search_with_hub_as_backend title: Vector Search on Hugging Face with the Hub as Backend - title: Agents Recipes isExpanded: false sections: - local: agents title: Build an agent with tool-calling superpowers using smolagents - local: agent_rag title: Agentic RAG - turbocharge your RAG with query reformulation and self-query - local: agent_text_to_sql title: Agent for Text-to-SQL with automatic error correction - local: agent_data_analyst title: Data analyst agent - get your data's insights in the blink of an eye - local: multiagent_web_assistant title: Have several agents collaborate in a multi-agent hierarchy - local: multiagent_rag_system title: Multi-agent RAG System 🤖🤝🤖 - local: mongodb_smolagents_multi_micro_agents title: MongoDB + SmolAgents Multi-Micro Agents to facilitate a data driven order-delivery AI agent - title: Enterprise Hub Cookbook isExpanded: True sections: - local: enterprise_cookbook_overview title: Overview - local: enterprise_cookbook_dev_spaces title: Interactive Development In HF Spaces - local: enterprise_hub_serverless_inference_api title: Inference API (Serverless) - local: enterprise_dedicated_endpoints title: Inference Endpoints (Dedicated) - local: enterprise_cookbook_argilla title: Data annotation with Argilla Spaces - local: enterprise_cookbook_gradio title: Creating demos with Spaces and Gradio