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gordon-posit
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Parent(s):
95bc557
Use sidebar layout
Browse files- src/_quarto.yml +7 -5
- src/index.qmd +6 -6
src/_quarto.yml
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@@ -3,15 +3,17 @@ project:
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website:
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title: "Open-Source AI Cookbook"
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- href: index.qmd
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text:
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- notebooks/automatic_embedding.ipynb
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- notebooks/faiss.ipynb
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- notebooks/single_gpu.ipynb
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- notebooks/rag_zephyr_langchain.ipynb
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- notebooks/advanced_rag.ipynb
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- notebooks/rag_evaluation.ipynb
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website:
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title: "Open-Source AI Cookbook"
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sidebar:
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style: "docked"
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search: true
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contents:
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- href: index.qmd
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text: About
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- notebooks/automatic_embedding.ipynb
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- notebooks/faiss.ipynb
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- notebooks/single_gpu.ipynb
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- section: RAG
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contents:
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- notebooks/rag_zephyr_langchain.ipynb
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- notebooks/advanced_rag.ipynb
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- notebooks/rag_evaluation.ipynb
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src/index.qmd
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@@ -15,12 +15,12 @@ You can also use Quarto to write [books](https://quarto.org/docs/books/), create
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Check out the recently added notebooks:
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- [Automatic Embeddings with TEI through Inference Endpoints](
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- [Simple RAG for GitHub issues using Hugging Face Zephyr and LangChain](rag_zephyr_langchain)
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- [Embedding multimodal data for similarity search using π€ transformers, π€ datasets and FAISS](
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- [Fine-tuning a Code LLM on Custom Code on a single GPU](
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- [RAG Evaluation Using Synthetic data and LLM-As-A-Judge](rag_evaluation)
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- [Advanced RAG on HuggingFace documentation using LangChain](advanced_rag)
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You can also check out the notebooks in the cookbook's [GitHub repo](https://github.com/huggingface/cookbook).
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Check out the recently added notebooks:
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- [Automatic Embeddings with TEI through Inference Endpoints](notebooks/automatic_embedding.ipynb)
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- [Simple RAG for GitHub issues using Hugging Face Zephyr and LangChain](notebooks/rag_zephyr_langchain.ipynb)
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- [Embedding multimodal data for similarity search using π€ transformers, π€ datasets and FAISS](notebooks/faiss.ipynb)
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- [Fine-tuning a Code LLM on Custom Code on a single GPU](notebooks/single_gpu.ipynb)
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- [RAG Evaluation Using Synthetic data and LLM-As-A-Judge](notebooks/rag_evaluation.ipynb)
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- [Advanced RAG on HuggingFace documentation using LangChain](notebooks/advanced_rag.ipynb)
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You can also check out the notebooks in the cookbook's [GitHub repo](https://github.com/huggingface/cookbook).
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