While theoretical learning is crucial, hands-on knowledge through practical examples is equally essential. The application of concepts in real-world scenarios enhances understanding and proficiency in a way that theoretical knowledge alone cannot achieve. ~Unknown
Example Name | Level | Description | Link |
---|---|---|---|
TinyLama.ipynb | Beginner | Load open source TinyLlama-1.1B-Chat-v0.6 for Text completion | My First LLM Experiment |
Vector_Example.ipynb | Beginner | Vector Basic | Vector Databases |
Chroma_Example_1.ipynb | Beginner | How to use ChromaDB | Vector Databses |
Chroma_Example_2.ipynb | Beginner | How to Use ChromaDB advanced | Vector Databases |
AlBert.ipynb | Intermediate | Implementaiton of Bert Model | LLM Models Encyclopedia |
Cerebras.ipynb | Beginner | facilitate research into LLM scaling laws using open architectures and data set |
LLM Models Encyclopedia |
cookGPT.ipynb | Intermediate | calling custom fine tuned model on open ai | |
cookGPT_NewRecipe.ipynb | Advanced | asking to create new recipe ( prompting) | |
CookGPT_SQL.ipynb | Intermediate | LLM for SQL queries | Ai for SQL |
dataset_experiment.ipynb | Beginner | Play around with open source data set from hugging face or kaggle |
|
distilbert.ipynb | Beginner | Another variation of bERT | LLM Models Encyclopedia |
Examples_BERT.ipynb | Beginner | bERt examples | LLM Models Encyclopedia |
Flan_T5.ipynb | Beginner | Google T Flan | LLM Models Encyclopedia |
Llama_CookGPT_AutoTrain_LLM.ipynb | Intermediate | Fine Tuning using Hugging Face Autotrain Advaned | |
MovieReview.ipynb | Beginner | Basic Open AI example | |
NLLB.ipynb | Intermediate | Indic Languages Translation | LLM for Indic Languages |
PredictionImage.ipynb | Beginner | Prediction based on image data using google deplot | LLM Models Encyclopedia |
Quantized_CookGPT.ipynb | Beginner | Quantized models for 8 Bit loading | Quantize a model |
TrainCustom.ipynb | Intermediate | Fine Tune using Trainer ApI from Hugging Face | |
Using_CookGPT_AutoTrain_LLM.ipynb | Intermediate | Fine tune large model | Auto Train Advanced |
finetuning.ipynb | Intermediate | Fine Tune on Open AI using Colab | |
phi_2.ipynb | Beginner | Microsoft Phi LLM example | LLM Models Encyclopedia |
CookGPT_SQL_Langchain.ipynb | Intermediate | SQL , LLM Model and Langchain example | Ai for SQL |
Generate_Free_video.ipynb | Intermediate | Video generation using AnimateDiff | Free Images in Code |
Generate_Image_Free.ipynb | Intermediate | Image generation using openjourney - stable diff | Free Images in Code |
Stable_Diff.ipynb | Intermediate | Image Generation using Stable Diff | Free Images in Code |
Generate_Data.ipynb | Beginner | Generate Synthetic Data using Open Ai | |
Face_ID.ipynb | Intermediate | Face Id recognization using InsightFace | Free Images in Code |
Gradio.ipynb | Intermediate | Webapp using Gradio and LLM on Colab | Use Gradio and LLM |
embeddings.ipynb | Intermediate | Embeddings and Quantizaton | Model Quantization |
gradio_advanced.ipynb | Intermediate | How to Quantize a model | Use Gradio and Quantized model |
image_QA.ipynb | Intermediate | Recognize objects in image | Detect Objects in Images |
face_recognize.ipynb | Intermediate | Face Detection and Recognization | Face Detection and Recognization |
Integrade examples with LLM using Langchain, Huggingface pipeline, LamaIndex, or Haystack
Example Name | Library | Description | Link |
---|---|---|---|
TinyLama.ipynb | Langchain | Load open source TinyLlama-1.1B-Chat-v0.6 for Text completion | My First LLM Experiment |
Vector_Example.ipynb | Pipeline | Vector Basic | Vector Databases |
Deployments using Git Hub Codespace, RunPod, Vast.ai, Together.ai, Paperspace
Manifest , Promptify
Colab, Kaggle, LmStudio