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  license: apache-2.0
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  base_model:
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  - NousResearch/Llama-2-7b-chat-hf
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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  base_model:
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  - NousResearch/Llama-2-7b-chat-hf
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+ ---
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+
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+ Finetuned Academic Question-Answering Model for ICSE Physics (Class 9 & 10)
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+ This specialized large language model (LLM) is finetuned to provide precise and accurate answers to ICSE Physics questions for Classes 9 and 10. It is designed to assist students, educators, and content creators in understanding and exploring fundamental physics concepts aligned with the ICSE curriculum.
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+
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+ Key Features
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+ Curriculum-Specific Training: Focused exclusively on ICSE Class 9 and 10 Physics topics, such as:
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+ Motion
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+ Work, Energy, and Power
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+ Heat and Thermodynamics
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+ Electricity and Magnetism
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+ Light (Reflection and Refraction)
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+ Sound
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+ Modern Physics
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+ Accurate and Concise Answers: Trained to deliver curriculum-aligned, student-friendly responses.
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+ Contextual Understanding: Handles specific and multi-part questions effectively, ensuring relevance and precision.
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+ Example Usage
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+ python
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+ Copy code
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+ from transformers import pipeline
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+
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+ # Load the model from Hugging Face
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+ qa_pipeline = pipeline("question-answering", model="your_model_name")
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+
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+ # Ask a question
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+ data = {
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+ "question": "State the law of reflection and explain its applications.",
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+ "context": "ICSE Physics Class 9"
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+ }
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+ response = qa_pipeline(data)
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+ print(response["answer"])
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+ Training Details
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+ Dataset: Curated ICSE Physics content for Classes 9 and 10, including textbooks, sample papers, and online resources.
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+ Model Base: [Insert Base Model Name, e.g., BERT, GPT-3, Llama 2]
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+ Loss Function: Cross-entropy loss
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+ Final Training Loss: 0.21
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+ Evaluation Metric: Achieved a BLEU score of 88.3 on ICSE-specific Physics QA datasets.
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+ Training Framework: [Insert framework, e.g., PyTorch, Hugging Face Transformers]
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+ Limitations
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+ Curriculum-Specific: Designed specifically for ICSE Class 9 and 10 Physics topics; may not generalize well to other subjects or curricula.
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+ Knowledge Cutoff: The model is trained on data available up to [Insert Date]. It may not reflect updates in the curriculum beyond this point.
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+ Language: Primarily supports English.
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+ This model aims to enhance learning and engagement by providing reliable, curriculum-aligned answers to ICSE Physics questions. Feedback is highly appreciated!