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| - title: Open-Source AI Cookbook | ||
| isExpanded: True | ||
| sections: | ||
| - local: index | ||
| title: Open-Source AI Cookbook | ||
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| - title: LLM Recipes | ||
| 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_evaluation | ||
| title: RAG Evaluation | ||
| - local: llm_judge | ||
| title: Using LLM-as-a-judge for an automated and versatile evaluation | ||
| - local: index | ||
| title: Overview | ||
|
|
||
| - title: Diffusion Recipes | ||
| sections: | ||
| - local: stable_diffusion_interpolation | ||
| title: Stable Diffusion Interpolation | ||
| - 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_evaluation | ||
| title: RAG Evaluation | ||
| - local: llm_judge | ||
| title: Using LLM-as-a-judge for an automated and versatile evaluation | ||
| - 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: 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: 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: llm_gateway_pii_detection | ||
| title: LLM Gateway for PII Detection | ||
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| - 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 | ||
|
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||
| - title: Multimodal Recipes | ||
| 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 | ||
|
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| - title: LLM and RAG recipes with other Libraries | ||
| sections: | ||
| - 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: 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: structured_generation | ||
| title: RAG with source highlighting using Structured generation | ||
| - title: Diffusion Recipes | ||
| isExpanded: false | ||
| sections: | ||
| - local: stable_diffusion_interpolation | ||
| title: Stable Diffusion Interpolation | ||
|
|
||
| - title: Computer Vision | ||
| sections: | ||
| - local: fine_tuning_vit_custom_dataset | ||
| title: Fine-tuning a Vision Transformer Model With a Custom Biomedical Dataset | ||
| - 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 | ||
|
|
||
| - title: Agents Recipes | ||
| isExpanded: false | ||
| sections: | ||
| - local: agents | ||
| title: Build an agent with tool-calling superpowers using Transformers Agents | ||
| - local: agent_rag | ||
| title: Agentic RAG - turbocharge your RAG with query reformulation and self-query | ||
|
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| - title: Agents | ||
| - title: Enterprise Hub Cookbook | ||
| isExpanded: True | ||
| sections: | ||
| - local: agents | ||
| title: Build an agent with tool-calling superpowers using Transformers Agents | ||
| - local: agent_rag | ||
| title: Agentic RAG - turbocharge your RAG with query reformulation and self-query | ||
| - 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 |
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