Update README

google-gemini · Oct 14, 2024 · 22ef3d6 · 22ef3d6
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@@ -24,10 +24,12 @@ You can find the Gemma models on GitHub, Hugging Face models, Kaggle, Google Clo
 | LangChain    | This [tutorial](partner-quickstarts/gemma-langchain.ipynb) shows you how to get started with Gemma and LangChain, running in Google Cloud or in your Colab environment.                      |
 | MongoDB      | This [article](partner-quickstarts/rag_with_hugging_face_gemma_mongodb.ipynb) presents how to leverage Gemma as the foundation model in a retrieval-augmented generation pipeline or system. |
 
-## Workshops
-| Notebook                                                                                                                    | Description                                         |
-| --------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------- |
-| [Workshop_How_to_Fine_tuning_Gemma.ipynb](Workshops/Workshop_How_to_Fine_tuning_Gemma.ipynb/Keras_Gemma_2_Quickstart.ipynb) | Recommended finetuning notebook for getting started |
+## Workshops and technical talks
+| Notebook                                                                                                                    | Description                                                                                                                                        |
+| --------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [Workshop_How_to_Fine_tuning_Gemma.ipynb](Workshops/Workshop_How_to_Fine_tuning_Gemma.ipynb/Keras_Gemma_2_Quickstart.ipynb) | Recommended finetuning notebook for getting started                                                                                                |
+| [Self_extend_Gemma.ipynb](Gemma/Self_extend_Gemma.ipynb)                                                                    | Self-extend context window for Gemma in the I/O 2024 [Keras talk](https://www.youtube.com/watch?v=TV7qCk1dBWA)                                     |
+| [Gemma_control_vectors.ipynb](Gemma/Gemma_control_vectors.ipynb)                                                            | Implement [control vectors](https://arxiv.org/abs/2310.01405) with Gemma in the I/O 2024 [Keras talk](https://www.youtube.com/watch?v=TV7qCk1dBWA) |
 
 ## Accompanying notebooks for the Build with AI video series
 | Folder                                                      |
@@ -51,7 +53,6 @@ You can find the Gemma models on GitHub, Hugging Face models, Kaggle, Google Clo
 | [Chat_and_distributed_pirate_tuning.ipynb](Gemma/Chat_and_distributed_pirate_tuning.ipynb)                           | Chat with Gemma 7B and finetune it so that it generates responses in pirates' tone.                                                                                                     |
 | [gemma_inference_on_tpu.ipynb](Gemma/gemma_inference_on_tpu.ipynb)                                                   | Basic inference of Gemma with JAX/Flax on TPU.                                                                                                                                          |
 | [gemma_data_parallel_inference_in_jax_tpu.ipynb](Gemma/gemma_data_parallel_inference_in_jax_tpu.ipynb)               | Parallel inference of Gemma with JAX/Flax on TPU.                                                                                                                                       |
-| [Gemma_control_vectors.ipynb](Gemma/Gemma_control_vectors.ipynb)                                                     | Implement [control vectors](https://arxiv.org/abs/2310.01405) with Gemma in the I/O 2024 [Keras talk](https://www.youtube.com/watch?v=TV7qCk1dBWA).                                     |
 | [Gemma_Basics_with_HF.ipynb](Gemma/Gemma_Basics_with_HF.ipynb)                                                       | Load, run, finetune and deploy Gemma using [Hugging Face](https://huggingface.co/).                                                                                                     |
 | [Gemma_with_Langfun_and_LlamaCpp.ipynb](Gemma/Gemma_with_Langfun_and_LlamaCpp.ipynb)                                 | Leverage [Langfun](https://github.com/google/langfun) to seamlessly integrate natural language with programming using Gemma 2 and [LlamaCpp](https://github.com/ggerganov/llama.cpp).   |
 | [Gemma_with_Langfun_and_LlamaCpp_Python_Bindings.ipynb](Gemma/Gemma_with_Langfun_and_LlamaCpp_Python_Bindings.ipynb) | Leverage [Langfun](https://github.com/google/langfun) for smooth language-program interaction with Gemma 2 and [llama-cpp-python](https://github.com/abetlen/llama-cpp-python).         |
@@ -71,8 +72,6 @@ You can find the Gemma models on GitHub, Hugging Face models, Kaggle, Google Clo
 | [Prompt_chaining.ipynb](Gemma/Prompt_chaining.ipynb)                                                                 | Illustrate prompt chaining and iterative generation with Gemma.                                                                                                                         |
 | [LangChain_chaining.ipynb](Gemma/LangChain_chaining.ipynb)                                                           | Illustrate LangChain chaining  with Gemma.                                                                                                                                              |
 | [Advanced_Prompting_Techniques.ipynb](Gemma/Advanced_Prompting_Techniques.ipynb)                                     | Illustrate advanced prompting techniques with Gemma.                                                                                                                                    |
-| **Long context**                                                                                                     |                                                                                                                                                                                         |
-| [Self_extend_Gemma.ipynb](Gemma/Self_extend_Gemma.ipynb)                                                             | Self-extend context window for Gemma in the I/O 2024 [Keras talk](https://www.youtube.com/watch?v=TV7qCk1dBWA).                                                                         |
 | **RAG**                                                                                                              |                                                                                                                                                                                         |
 | [RAG_with_ChromaDB.ipynb](Gemma/RAG_with_ChromaDB.ipynb)                                                             | Build a Retrieval Augmented Generation (RAG) system with Gemma using [ChromaDB](https://www.trychroma.com/) and [Hugging Face](https://huggingface.co/).                                |
 | [Minimal_RAG.ipynb](Gemma/Minimal_RAG.ipynb)                                                                         | Minimal example of building a RAG system with Gemma using [Google UniSim](https://github.com/google/unisim) and [Hugging Face](https://huggingface.co/).                                |