Create README.md

README.md

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+---
+license: mit
+metrics:
+- accuracy
+base_model:
+- openai-community/gpt2
+- LLMasterLL/AbNovobench
+library_name: transformers
+tags:
+- text-generation-inference
+- chatbot
+- causal-lm
+- educational
+- AI tutor
+---
+# AI Tutor Model v2
+
+**Model:** `ai-tutor-model-v2`  
+**Author:** mah567  
+**License:** MIT / Apache 2.0  
+**Tags:** chatbot, question-answering, educational, AI tutor
+
+---
+
+## Model Description
+
+`ai-tutor-model-v2` is a fine-tuned causal language model designed to answer educational questions. It is trained on a custom dataset of Q&A pairs to assist students and learners with explanations and solutions.
+
+---
+
+## Intended Use
+
+- Answering educational questions.
+- Providing explanations for simple queries.
+- Assisting in tutoring and learning scenarios.
+
+**Not intended for:**
+- Medical, legal, or financial advice.
+- Sensitive personal data processing.
+
+---
+
+## How to Use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+# Load the model
+tokenizer = AutoTokenizer.from_pretrained("mah567/ai-tutor-model-v2")
+model = AutoModelForCausalLM.from_pretrained("mah567/ai-tutor-model-v2")
+
+# Create a text-generation pipeline
+tutor = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Ask a question
+response = tutor("What is the capital of France?", max_length=50)
+print(response[0]['generated_text'])