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  - llama
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  - trl
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  - sft
 
 
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  ---
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- # Uploaded model
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- - **Developed by:** rahulvk007
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- - **License:** apache-2.0
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- - **Finetuned from model :** unsloth/SmolLM2-135M
 
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- This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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- [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - llama
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  - trl
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  - sft
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+ datasets:
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+ - rahulvk007/quenumber_extraction_v2
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  ---
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+ # ExtractQueNumberMini Model
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+ - **Developed by:** [rahulvk007](https://github.com/rahulvk007) ([rahulvk.com](https://www.rahulvk.com))
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+ - **License:** [Apache-2.0](https://opensource.org/licenses/Apache-2.0)
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+ - **Base Model:** [unsloth/SmolLM2-135M](https://huggingface.co/unsloth/SmolLM2-135M)
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+ - **Finetuning**: Optimized with [Unsloth](https://github.com/unslothai/unsloth) and [Hugging Face's TRL library](https://github.com/huggingface/trl)
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+ This model has been fine-tuned for quick extraction of question numbers from OCRed handwritten text. It is designed to run efficiently on CPU due to its compact size.
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+ ### Model Usage
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+
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+ To use this model, set the system prompt to the following:
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+
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+ > **Extract the question number from the given text. Your response should be just an integer representing the question number. Do not provide any explanation or context. Just the number.**
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+
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+ ### Inference Code Example
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ checkpoint = "rahulvk007/ExtractQueNumberMini"
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+ device = "cpu" # change to "cuda" for GPU
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+
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+ tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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+ model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
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+
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+ alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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+
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+ ### Instruction:
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+ {}
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+
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+ ### Input:
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+ {}
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+
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+ ### Response:
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+ {}"""
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+
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+ inputs = tokenizer(
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+ [
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+ alpaca_prompt.format(
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+ "Extract the question number from the given text. Your response should be just an integer which is the question number. Do not provide any explanation or context. Just the number.",
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+ "<Give OCR Text here>",
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+ "",
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+ )
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+ ],
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+ return_tensors="pt"
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+ ).to(device)
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+
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+ outputs = model.generate(**inputs, max_new_tokens=64, use_cache=True)
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+ print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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+ ```
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+
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+ ### Datasets
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+
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+ The model was fine-tuned on [rahulvk007/quenumber_extraction_v2](https://huggingface.co/datasets/rahulvk007/quenumber_extraction_v2), specifically curated for this task.
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+
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+ ---
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+
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+ [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)