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--- |
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library_name: transformers |
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datasets: |
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- bitext/Bitext-customer-support-llm-chatbot-training-dataset |
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--- |
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# Fine-Tuned GEMMA Model for Chatbot |
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This repository hosts the fine-tuned version of the GEMMA 1.1-2B model, specifically fine-tuned for a customer support chatbot use case. |
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## Model Description |
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The GEMMA 1.1-2B model has been fine-tuned on the [Bitext Customer Support Dataset](https://huggingface.co/datasets/bitext/customer-support-l1m-chatbot-training-dataset) for answering customer support queries. The fine-tuning process involved adjusting the model's weights based on question and answer pairs, which should enable it to generate more accurate and contextually relevant responses in a conversational setting. |
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## How to Use |
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You can use this model directly with a pipeline for text generation: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("your-username/your-model-name") |
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model = AutoModelForCausalLM.from_pretrained("your-username/your-model-name") |
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chatbot = pipeline("text-generation", model=model, tokenizer=tokenizer) |
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response = chatbot("How can I cancel my order?") |
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print(response[0]['generated_text']) |
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``` |
