Create README.md

README.md

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+---
+language: 
+- en
+tags:
+- dialogue
+- conversation-generator
+- flan-t5-base
+- fine-tuned
+license: apache-2.0
+datasets:
+- kaggle-dialogue-dataset
+---
+
+# Omaratef3221/flan-t5-base-dialogue-generator
+
+## Model Description
+This model is a fine-tuned version of Google's `t5` specifically tailored for generating realistic and engaging dialogues or conversations. 
+It has been trained to capture the nuances of human conversation, making it highly effective for applications requiring conversational AI capabilities.
+
+## Intended Use
+`Omaratef3221/flan-t5-base-dialogue-generator` is ideal for developing chatbots, virtual assistants, and other applications where generating human-like dialogue is crucial. 
+It can also be used for research and development in natural language understanding and generation.
+
+## How to Use
+You can use this model directly with the transformers library as follows:
+
+```python
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model_name = "Omaratef3221/flan-t5-base-dialogue-generator"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+prompt = '''
+Generate a dialogue between two people about the following topic:
+A local street market bustles with activity, #Person1# tries exotic food for the first time, and #Person2#, familiar with the cuisine, offers insights and recommendations.
+Dialogue:
+'''
+# Generate a response to an input statement
+input_ids = tokenizer(prompt, return_tensors='pt').input_ids
+output = model.generate(input_ids, top_p = 0.6, do_sample=True, temperature = 1.2, max_length = 512)
+print(tokenizer.decode(output[0], skip_special_tokens=True).replace('. ', '.\n'))
+