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ashishpatel26/LLM-Finetuning

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Stars

★ 3.0k

Forks

⑂ 769

Language

Jupyter Notebook

Topic

AI Tools

License

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Updated

1.0y ago

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Homepage

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A look at ashishpatel26/LLM-Finetuning: 3.0k stars on GitHub, written primarily in Jupyter Notebook, tracked under the AI Tools category. LLM Finetuning with peft

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Stars★ 3.0k

Forks⑂ 769

LanguageJupyter Notebook

TopicAI Tools

License—

Homepage—

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Top 21 contributors to ashishpatel26/LLM-Finetuning

Notebook Title	Description	Colab Badge
1. Efficiently Train Large Language Models with LoRA and Hugging Face	Details and code for efficient training of large language models using LoRA and Hugging Face.
2. Fine-Tune Your Own Llama 2 Model in a Colab Notebook	Guide to fine-tuning your Llama 2 model using Colab.
3. Guanaco Chatbot Demo with LLaMA-7B Model	Showcase of a chatbot demo powered by LLaMA-7B model.
4. PEFT Finetune-Bloom-560m-tagger	Project details for PEFT Finetune-Bloom-560m-tagger.
5. Finetune_Meta_OPT-6-1b_Model_bnb_peft	Details and guide for finetuning the Meta OPT-6-1b Model using PEFT and Bloom-560m-tagger.
6.Finetune Falcon-7b with BNB Self Supervised Training	Guide for finetuning Falcon-7b using BNB self-supervised training.
7.FineTune LLaMa2 with QLoRa	Guide to fine-tune the Llama 2 7B pre-trained model using the PEFT library and QLoRa method
8.Stable_Vicuna13B_8bit_in_Colab	Guide of Fine Tuning Vecuna 13B_8bit
9. GPT-Neo-X-20B-bnb2bit_training	Guide How to train the GPT-NeoX-20B model using bfloat16 precision
10. MPT-Instruct-30B Model Training	MPT-Instruct-30B is a large language model from MosaicML that is trained on a dataset of short-form instructions. It can be used to follow instructions, answer questions, and generate text.
11.RLHF_Training_for_CustomDataset_for_AnyModel	How train a Model with RLHF training on any LLM model with custom dataset
12.Fine_tuning_Microsoft_Phi_1_5b_on_custom_dataset(dialogstudio)	How train a model with trl SFT Training on Microsoft Phi 1.5 with custom
13. Finetuning OpenAI GPT3.5 Turbo	How to finetune GPT 3.5 on your own data
14. Finetuning Mistral-7b FineTuning Model using Autotrain-advanced	How to finetune Mistral-7b using autotrained-advanced
15. RAG LangChain Tutorial	How to Use RAG using LangChain
16. Knowledge Graph LLM with LangChain PDF Question Answering	How to build knowledge graph with pdf question answering
17. Text to Knolwedge Graph with OpenAI Function with Neo4j and Langchain Agent Question Answering	How to build knowledge graph from text or Pdf Document with pdf question Answering
18. Convert the Document to Knowledgegraph using Langchain and Openai	This notebook is help you to understand how easiest way you can convert your any documents into Knowledgegraph for your next RAG based Application
19. How to train a 1-bit Model with LLMs?	This notebook is help you to train a model with 1-bit and 2-bit quantization method using hqq framework
20.Alpaca_+_Gemma2_9b_Unsloth_2x_faster_finetuning	This notebook is help you to train a model with gemma2 9b
21.RAG Pipeline Evaluation Using MLFLOW Best Industry Practice	This notebook provides a comprehensive guide to evaluating the 21 RAG (Retrieve-then-Answer Generation) pipeline using MLFLOW, adhering to best industry practices.
22. Evaluate a Hugging Face LLM with `mlflow.evaluate()`	This notebook provides a comprehensive guide on evaluating a Hugging Face Language Learning Model (LLM) using mlflow_evaluate.
23. Optimizing LLMs with Cache-Augmented-Generation	Explores techniques from the research paper Cache-Augmented Generation (CAG) to enhance LLM efficiency and response speed using caching strategies.

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ashishpatel26/LLM-Finetuning (ashishpatel26/LLM-Finetuning) is a Jupyter Notebook project on GitHub. From the project's own README: LLM Finetuning with peft

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