Keras_Gemma_2_Quickstart.ipynb |
Gemma 2 pre-trained 9B model quickstart tutorial with Keras. |
Keras_Gemma_2_Quickstart_Chat.ipynb |
Gemma 2 instruction-tuned 9B model quickstart tutorial with Keras. Referenced in this blog. |
Gemma inference with Flax/NNX |
Gemma 1 inference with Flax/NNX framework (linking to Flax documentation) |
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 |
Basic inference of Gemma with JAX/Flax on TPU. |
gemma_data_parallel_inference_in_jax_tpu.ipynb |
Parallel inference of Gemma with JAX/Flax on TPU. |
Gemma_Basics_with_HF.ipynb |
Load, run, finetune and deploy Gemma using Hugging Face. |
Gemma_with_Langfun_and_LlamaCpp.ipynb |
Leverage Langfun to seamlessly integrate natural language with programming using Gemma 2 and LlamaCpp. |
Gemma_with_Langfun_and_LlamaCpp_Python_Bindings.ipynb |
Leverage Langfun for smooth language-program interaction with Gemma 2 and llama-cpp-python. |
Guess_the_word.ipynb |
Play a word guessing game with Gemma using Keras. |
Game_Design_Brainstorming.ipynb |
Use Gemma to brainstorm ideas during game design using Keras. |
Translator_of_Old_Korean_Literature.ipynb |
Use Gemma to translate old Korean literature using Keras. |
Gemma2_on_Groq.ipynb |
Leverage the free Gemma 2 9B IT model hosted on Groq (super fast speed). |
Run_with_Ollama.ipynb |
Run Gemma models using Ollama. |
Run_with_Ollama_Python.ipynb |
Run Gemma models using Ollama Python library. |
Using_Gemma_with_Llamafile.ipynb |
Run Gemma models using Llamafile. |
Using_Gemma_with_LlamaCpp.ipynb |
Run Gemma models using LlamaCpp. |
Using_Gemma_with_LocalGemma.ipynb |
Run Gemma models using Local Gemma. |
Using_Gemma_with_mistral_rs.ipynb |
Run Gemma models using mistral.rs. |
Using_Gemini_and_Gemma_with_RouteLLM.ipynb |
Route Gemma and Gemini models using RouteLLM. |
Using_Gemma_with_SGLang.ipynb |
Run Gemma models using SGLang. |
Using_Gemma_with_Xinference.ipynb |
Run Gemma models using Xinference. |
Constrained_generation_with_Gemma.ipynb |
Constrained generation with Gemma models using LlamaCpp and Guidance. |
Integrate_with_Mesop.ipynb |
Integrate Gemma with Google Mesop. |
Integrate_with_OneTwo.ipynb |
Integrate Gemma with Google OneTwo. |
Deploy_with_vLLM.ipynb |
Deploy a Gemma model using vLLM. |
Deploy_Gemma_in_Vertex_AI.ipynb |
Deploy a Gemma model using Vertex AI. |
Prompting |
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Prompt_chaining.ipynb |
Illustrate prompt chaining and iterative generation with Gemma. |
LangChain_chaining.ipynb |
Illustrate LangChain chaining with Gemma. |
Advanced_Prompting_Techniques.ipynb |
Illustrate advanced prompting techniques with Gemma. |
RAG |
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RAG_with_ChromaDB.ipynb |
Build a Retrieval Augmented Generation (RAG) system with Gemma using ChromaDB and Hugging Face. |
Minimal_RAG.ipynb |
Minimal example of building a RAG system with Gemma using Google UniSim and Hugging Face. |
RAG_PDF_Search_in_multiple_documents_on_Colab.ipynb |
RAG PDF Search in multiple documents using Gemma 2 2B on Google Colab. |
Using_Gemma_with_LangChain.ipynb |
Examples to demonstrate using Gemma with LangChain. |
Using_Gemma_with_Elasticsearch_and_LangChain.ipynb |
Example to demonstrate using Gemma with Elasticsearch, Ollama and LangChain. |
Gemma_with_Firebase_Genkit_and_Ollama.ipynb |
Example to demonstrate using Gemma with Firebase Genkit and Ollama |
Gemma_RAG_LlamaIndex.ipynb |
RAG example with LlamaIndex using Gemma. |
Finetuning |
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Finetune_with_Axolotl.ipynb |
Finetune Gemma using Axolotl. |
Finetune_with_XTuner.ipynb |
Finetune Gemma using XTuner. |
Finetune_with_LLaMA_Factory.ipynb |
Finetune Gemma using LLaMA-Factory. |
Finetune_with_Torch_XLA.ipynb |
Finetune Gemma using PyTorch/XLA. |
Finetune_with_JORA.ipynb |
Finetune Gemma using JORA. |
Finetune_with_Unsloth.ipynb |
Finetune Gemma using Unsloth. |
Finetune_with_LitGPT.ipynb |
Finetune Gemma using LitGPT. |
Finetune_with_CALM.ipynb |
Finetune Gemma using CALM. |
Finetuning_Gemma_for_Function_Calling.ipynb |
Finetuning Gemma for Function Calling using PyTorch/XLA. |
Custom_Vocabulary.ipynb |
Demonstrate how to use a custom vocabulary "<unused[0-98]>" tokens in Gemma. |
Alignment |
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Aligning_DPO_Gemma_2b_it.ipynb |
Demonstrate how to align a Gemma model using DPO (Direct Preference Optimization) with Hugging Face TRL. |
Evaluation |
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Gemma_evaluation.ipynb |
Demonstrate how to use Eleuther AI's LM evaluation harness to perform model evaluation on Gemma. |
Mobile |
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Gemma on Android |
Android app to deploy fine-tuned Gemma-2B-it model using MediaPipe LLM Inference API. |