How to start [**testing models on Hugging Face.pdf**](uploads/8fefb32f55207dd19e6b4158697f0eea/testing_models_on_Hugging_Face.pdf)(for beginners)
Simple approach to [**Testing LLM Language.**pdf](uploads/2d20d28547294864f01ef0e81bd3f43f/Testing_LLM_Language.pdf) capabilities (models from Hugging Face)
Simple approach to [\*\*Testing LLM Language.\*\*pdf](uploads/2d20d28547294864f01ef0e81bd3f43f/Testing_LLM_Language.pdf) capabilities (models from Hugging Face)
A **guide to Open source LLMs** ([Part 1.pdf](uploads/9dbdb1c88d65215006f971cc29bd1e2a/Part_1.pdf)[Part 2.pdf](uploads/acc6443b6e0977ff7acda61c5778d6cd/Part_2.pdf) )
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@@ -22,6 +22,8 @@ Developing an [**Autonomous Dual-Chatbot System.pdf**](uploads/7afe69696c5f8b7e7
How to [**Fine-Tune local Llama 2 Model**](https://levelup.gitconnected.com/fine-tune-your-own-llama-2-model-in-a-colab-notebook-70b8c851d931) in a Colab Notebook
[**FineTuning the LLM.pdf**](uploads/fee1e5b9a4eea3889e561cb0402dc17d/FineTuning_the_LLM.pdf) Mistral 7B using LoRA and PEFT (Parameter Efficient Finetuning).
API using [**FastAPI for Local LLM**](https://artificialcorner.com/a-fastapi-for-your-local-llm-part-1-7bdfd2605b53)
[**Building a Reward Model**.pdf](uploads/5f57b475de79463da0ecb967a5e2cfcd/Building_a_Reward_Model.pdf) for your LLM Using RLHF in Python
