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--- |
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library_name: peft |
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base_model: unsloth/llama-2-7b |
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--- |
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Model Details |
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Original Model: unsloth/llama-2-7b |
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Fine-Tuned For: Azerbaijani language understanding and generation |
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Dataset Used: Azerbaijani translation of the Stanford Alpaca dataset |
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Fine-Tuning Method: Self-instruct method |
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This model, is part of the ["project/Barbarossa"](https://github.com/Alas-Development-Center/project-barbarossa) initiative, aimed at enhancing natural language processing capabilities for the Azerbaijani language. By fine-tuning this model on the Azerbaijani translation of the Stanford Alpaca dataset using the self-instruct method, we've made significant strides in improving AI's understanding and generation of Azerbaijani text. |
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__Our primary objective with this model is to offer insights into the feasibility and outcomes of fine-tuning large language models (LLMs) for the Azerbaijani language. The fine-tuning process was undertaken with limited resources, providing valuable learnings rather than creating a model ready for production use. Therefore, we recommend treating this model as a reference or a guide to understanding the potential and challenges involved in fine-tuning LLMs for specific languages. It serves as a foundational step towards further research and development rather than a direct solution for production environments.__ |
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This project is a proud product of the [Alas Development Center (ADC)](https://az.linkedin.com/company/alas-development-center?trk=ppro_cprof). We are thrilled to offer these finely-tuned large language models to the public, free of charge. |
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How to use? |
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``` |
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from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, pipeline |
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model_path = "alasdevcenter/az-llama2" |
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model = AutoModelForCausalLM.from_pretrained(model_path) |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200) |
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instruction = "Təbiətin qorunması " |
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formatted_prompt = f"""Aşağıda daha çox kontekst təmin edən təlimat var. Sorğunu adekvat şəkildə tamamlayan cavab yazın. |
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### Təlimat: |
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{instruction} |
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### Cavab: |
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""" |
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result = pipe(formatted_prompt) |
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print(result[0]['generated_text']) |
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``` |
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