Update README.md

README.md

@@ -10,3 +10,80 @@ datasets:
 pipeline_tag: text-generation
 base_model: tiiuae/falcon-7b
 ---
+
+# Model Card for Model ID
+
+Falcon-7B Fine-Tuned Chatbot Model
+This repository contains the fine-tuned Falcon-7B model for a chatbot application. The model has been fine-tuned using the PEFT method to provide robust responses for e-commerce customer support. It guides buyers in product selection, recommends sizes, checks product stock, suggests similar products, and presents reviews and social media video links.
+
+## Model Details
+
+- **Base Model**: Falcon 7B (tiiuae/falcon-7b)
+- **Fine-Tuning Method**: Parameter-Efficient Fine-Tuning (PEFT)
+- **Training Data** : Custom dataset including skincare e-commerce related dialogues. (UrFavB0i/skincare-ecommerce-FAQ)
+
+### Features
+
+- 24/7 customer support
+- Product selection guidance
+- Size recommendations
+- Product stock checks
+- Similar product suggestions
+- Reviews and social media video link presentation
+
+# Usage
+
+## Installation
+
+To use the model, you need to install the necessary dependencies. Make sure you have Python 3.7+ and pip installed.
+
+```
+pip install transformers
+pip install peft
+```
+
+## Loading the Model
+
+You can load the fine-tuned model using the transformers library:
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "your-huggingface-username/falcon-7b-chatbot"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+```
+
+# Example usage
+```
+inputs = tokenizer("Hello, how can I assist you today?", return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0]))
+```
+
+# Training Details
+
+The model was fine-tuned using the PEFT method on a dataset specifically curated for e-commerce scenarios. The training process involved:
+
+- **Data Preparation**: Gathering and preprocessing e-commerce-related dialogues.
+- **Fine-Tuning**: Training the base model using PEFT to adapt it to the specific needs of the e-commerce domain.
+
+# Evaluation
+
+The fine-tuned model was evaluated based on its ability to handle various e-commerce related queries, providing accurate and contextually appropriate responses.
+
+# Limitations
+
+While the model performs well in many scenarios, it might not handle extremely rare or out-of-domain queries perfectly. Continuous training and updating with more data can help improve its performance further.
+
+# Contributing
+
+We welcome contributions to improve this model. If you have any suggestions or find any issues, please create an issue or a pull request.
+
+# License
+
+This project is licensed under the Apache 2.0 License. See the [LICENSE] file for more details.
+
+# Acknowledgements
+
+Special thanks to the Falcon team and the creators of the tiiuae/falcon-7b model for providing the base model and the tools necessary for fine-tuning.
+