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NLP-Based Projects

This repository contains a collection of NLP (Natural Language Processing) projects that I have worked on by following YouTube tutorials. These projects were originally developed and saved in Google Colab and on my local hard drive. Now, I’m making them available here for open access and sharing with the community.

Projects Included

  • few-shot-text-classification-with-seftfi.ipynb: A few-shot learning model for text classification.
  • Bloom7 B with PEFT & bitsandbytes and LORA.ipynb: Fine-tuning the Bloom7 B model using PEFT, bitsandbytes, and LORA.
  • Fine_tuning_Llama2.ipynb: Fine-tuning the Llama2 model.
  • Gemma2_9b_with_Unsloth.ipynb: Project focusing on Gemma2 9B model with Unsloth.
  • DragGAN.ipynb: A project exploring the DragGAN model.
  • gpt-neo-bnb_4bit_training_with_inference.ipynb: Training and inference using the GPT-Neo model with 4-bit precision.
  • Llama_3_1_8b_-_Unsloth_2x_faster_finetuning.ipynb: Faster fine-tuning of Llama 3.1b model with Unsloth.
  • macaw-multi-angle-question-answering-model.ipynb: Multi-angle question answering using the Macaw model.
  • Mistral_Nemo_12b_Unsloth.ipynb: Fine-tuning the Mistral 12B model using Unsloth.
  • Mixtral_fine_tuning.ipynb: Fine-tuning the Mixtral model.
  • Phi_3_5_Instruct_Unsloth.ipynb: Instruction-based fine-tuning for Phi 3.5 model using Unsloth.
  • Phi_4_Unsloth.ipynb: Unsloth-based fine-tuning for Phi 4 model.
  • Qwen_2_5_Unsloth.ipynb: Fine-tuning Qwen 2.5 model using Unsloth.
  • Text_Emotion_Detection_in_Python.ipynb: Text emotion detection project in Python.
  • Text_to_Video_with_Diffusers.ipynb: Converting text to video using diffusers.
  • TinyLlama_fine_tuning.ipynb: Fine-tuning TinyLlama model.
  • Zephyr_7B_Alpha_inf.ipynb: Working with Zephyr 7B Alpha model.
  • stable_diffusion_2.0.ipynb: Exploring the Stable Diffusion 2.0 model.
  • Zero_Shot_Classification.ipynb: Zero-shot classification model for NLP tasks.
  • Llama_3_8b_instruct_finetune.ipynb: Instruction-based fine-tuning for Llama 3.8B model.

How to Use

  1. Clone this repository to your local machine: 
    git clone https://github.com/SoheilFM/Natural-Langaue-Processing.git

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

I would like to thank the creators of the YouTube tutorials for providing the foundational knowledge for these projects.

Feel free to fork, clone, or contribute to these projects!