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--- |
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language: |
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- en |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- text-generation-inference |
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datasets: |
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- UrFavB0i/skincare-ecommerce-FAQ |
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pipeline_tag: text-generation |
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base_model: tiiuae/falcon-7b |
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--- |
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# Model Card for Model ID |
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Falcon-7B Fine-Tuned Chatbot Model |
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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. |
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## Model Details |
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- **Base Model**: Falcon 7B (tiiuae/falcon-7b) |
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- **Fine-Tuning Method**: Parameter-Efficient Fine-Tuning (PEFT) |
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- **Training Data** : Custom dataset including skincare e-commerce related dialogues. (UrFavB0i/skincare-ecommerce-FAQ) |
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### Features |
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- 24/7 customer support |
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- Product selection guidance |
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- Size recommendations |
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- Product stock checks |
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- Similar product suggestions |
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- Reviews and social media video link presentation |
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# Usage |
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## Installation |
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To use the model, you need to install the necessary dependencies. Make sure you have Python 3.7+ and pip installed. |
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``` |
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pip install transformers |
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pip install peft |
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``` |
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## Loading the Model |
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You can load the fine-tuned model using the transformers library: |
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``` |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "your-huggingface-username/falcon-7b-chatbot" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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``` |
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# Example usage |
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``` |
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inputs = tokenizer("Hello, how can I assist you today?", return_tensors="pt") |
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outputs = model.generate(**inputs) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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# Training Details |
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The model was fine-tuned using the PEFT method on a dataset specifically curated for e-commerce scenarios. The training process involved: |
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- **Data Preparation**: Gathering and preprocessing e-commerce-related dialogues. |
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- **Fine-Tuning**: Training the base model using PEFT to adapt it to the specific needs of the e-commerce domain. |
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# Evaluation |
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The fine-tuned model was evaluated based on its ability to handle various e-commerce related queries, providing accurate and contextually appropriate responses. |
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# Limitations |
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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. |
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# Contributing |
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We welcome contributions to improve this model. If you have any suggestions or find any issues, please create an issue or a pull request. |
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# License |
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This project is licensed under the Apache 2.0 License. See the [LICENSE] file for more details. |
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# Acknowledgements |
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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. |
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