Added Rick Sanchez Bot created using Transformers

Natural Language Processing/rick_bot/README.md

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+# Rick and Morty ChatBot
+
+A conversational AI model based on Microsoft's DialoGPT-small, fine-tuned on Rick and Morty dialogue to create a chatbot that speaks in the style of the show's characters.
+
+## Overview
+
+This project uses the Hugging Face Transformers library to fine-tune Microsoft's DialoGPT model on Rick and Morty script data. The resulting model can engage in conversation while mimicking the show's distinctive dialogue style.
+
+## Requirements
+
+- Python 3.6+
+- PyTorch
+- Transformers
+- Pandas
+- NumPy
+- Kaggle API
+- tqdm
+- tensorboardX (if torch.utils.tensorboard is not available)
+
+## Installation
+
+1. Install the required packages:
+
+```bash
+pip install torch transformers pandas numpy kaggle tqdm tensorboardX
+```
+
+2. Set up Kaggle API credentials:
+
+- Place your `kaggle.json` file in the project directory
+- The script will automatically copy it to the correct location
+
+## Dataset
+
+The project uses the "Rick and Morty Scripts" dataset from Kaggle, which contains dialogue from the show. The data is processed to create conversation contexts with:
+
+- Current response
+- 7 previous responses for context
+- Automatic train/validation split (90/10)
+
+## Model Architecture
+
+- Base model: microsoft/DialoGPT-small
+- Architecture: GPT-2 based transformer
+- Fine-tuning approach: Causal language modeling (CLM)
+
+## Training
+
+The model is trained with the following parameters:
+
+- Batch size: 4 per GPU
+- Learning rate: 5e-5
+- Number of epochs: 3
+- Max sequence length: 512
+- Gradient accumulation steps: 1
+- Weight decay: 0.0
+- Warm-up steps: 0
+
+Training includes:
+
+- Automatic checkpointing
+- Tensorboard logging
+- Distributed training support
+- Mixed precision training (fp16) support
+- Gradient clipping
+
+## Usage
+
+### Training the Model
+
+```python
+from transformers import AutoModelWithLMHead, AutoTokenizer
+import torch
+
+# Initialize tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-small")
+model = AutoModelWithLMHead.from_pretrained("microsoft/DialoGPT-small")
+
+# Train the model
+main(trn_df, val_df)
+```
+
+### Using the Trained Model
+
+```python
+# Load the fine-tuned model
+tokenizer = AutoTokenizer.from_pretrained('microsoft/DialoGPT-small')
+model = AutoModelWithLMHead.from_pretrained('output-small')
+
+# Chat parameters
+max_length = 200
+no_repeat_ngram_size = 3
+top_k = 100
+top_p = 0.7
+temperature = 0.8
+
+# Generate responses
+chat_history_ids = model.generate(
+    input_ids,
+    max_length=max_length,
+    pad_token_id=tokenizer.eos_token_id,
+    no_repeat_ngram_size=no_repeat_ngram_size,
+    do_sample=True,
+    top_k=top_k,
+    top_p=top_p,
+    temperature=temperature
+)
+```
+
+## Generation Parameters
+
+The model uses the following parameters for response generation:
+
+- `max_length`: 200 tokens
+- `no_repeat_ngram_size`: 3 (prevents repetition of 3-grams)
+- `do_sample`: True (enables sampling-based generation)
+- `top_k`: 100 (limits vocabulary to top 100 tokens)
+- `top_p`: 0.7 (nucleus sampling parameter)
+- `temperature`: 0.8 (controls randomness of sampling)
+
+## Project Structure
+
+```
+.
+├── output-small/          # Directory for saved model checkpoints
+├── cached/               # Cache directory for processed datasets
+├── RickAndMortyScripts.csv  # Dataset file
+├── kaggle.json          # Kaggle API credentials
+└── training_args.bin    # Saved training arguments
+```
+
+## Evaluation
+
+The model is evaluated using perplexity on a held-out validation set. Evaluation is performed:
+
+- During training (if enabled)
+- After training
+- On all checkpoints (if specified)
+
+## Limitations
+
+- The model's responses are probabilistic and may not always be coherent
+- Training requires significant computational resources
+- The model may generate inappropriate content based on the training data
+- Response quality depends heavily on the input context
+
+## License
+
+Please refer to the original licenses for:
+
+- DialoGPT model
+- Rick and Morty dataset
+- Hugging Face Transformers library
+
+## Acknowledgments
+
+- Microsoft for the DialoGPT model
+- Hugging Face for the Transformers library
+- Kaggle and the dataset creator
+- Rick and Morty creators for the original content