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@@ -20,7 +20,7 @@ Before we start:
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Order of running files, the notebook establish the method of approaching the problem. Once we establish it, we use the scripts to run the method end to end.
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Order of running files, the notebook establish the method of approaching the problem. Once we establish it, we use the scripts to run the method end to end.
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-- Notebook 1: `Part_1_Data_Preperation.ipynb`
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+- Notebook 1: `Part_1_Data_Preparation.ipynb`
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- Script: `label_script.py`
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- Script: `label_script.py`
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- Notebook 2: `Part_2_Cleaning_Data_and_DB.ipynb`
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- Notebook 2: `Part_2_Cleaning_Data_and_DB.ipynb`
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- Notebook 3: `Part_3_RAG_Setup_and_Validation.ipynb`
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- Notebook 3: `Part_3_RAG_Setup_and_Validation.ipynb`
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@@ -32,7 +32,7 @@ Here's the detailed outline:
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In this step we start with an unlabelled dataset and use the image captioning capability of the model to write a description of the image and categorise it.
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In this step we start with an unlabelled dataset and use the image captioning capability of the model to write a description of the image and categorise it.
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-[Notebook for Step 1](./notebooks/Part_1_Data_Preperation.ipynb) and [Script for Step 1](./scripts/label_script.py)
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+[Notebook for Step 1](./notebooks/Part_1_Data_Preparation.ipynb) and [Script for Step 1](./scripts/label_script.py)
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To run the script (remember to set n):
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To run the script (remember to set n):
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```
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```
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@@ -111,6 +111,6 @@ Firstly, thanks to the author here for providing this dataset on which we base o
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- [Llama-3.2-11B-Vision-Instruct Model](https://www.llama.com/docs/how-to-guides/vision-capabilities/)
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- [Llama-3.2-11B-Vision-Instruct Model](https://www.llama.com/docs/how-to-guides/vision-capabilities/)
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- [Lance-db for vector database](https://lancedb.com)
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- [Lance-db for vector database](https://lancedb.com)
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-- [This Kaggle dataset]()
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+- [This Kaggle dataset](https://www.kaggle.com/datasets/agrigorev/clothing-dataset-full)
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- [HF Dataset](https://huggingface.co/datasets/Sanyam/MM-Demo) Since output of the model can be non-deterministic every time we run, we will use the uploaded dataset to give a universal experience
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- [HF Dataset](https://huggingface.co/datasets/Sanyam/MM-Demo) Since output of the model can be non-deterministic every time we run, we will use the uploaded dataset to give a universal experience
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- [Together API for demo](https://www.together.ai)
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- [Together API for demo](https://www.together.ai)
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Sanyam Bhutani