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--- |
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library_name: transformers |
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tags: [] |
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--- |
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# Model Card for Model ID |
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## Model Details |
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### Model Description |
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RoQLlama is a new lightweight Romanian language-adapted LLM with 7 billion parameters and quantized to 4 bits by employing the state-of-the-art quantized |
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LoRA (QLoRA) training technique. |
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- **Language:** Romanian |
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- **License:** Llama2 Community License Agreement |
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- **Finetuned from model:** Meta's Llama2 7B |
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### Model Sources |
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- **Paper:** https://arxiv.org/abs/2410.04269 |
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## How to Get Started with the Model |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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MODEL_NAME = "andreidima/Llama-2-7b-Romanian-qlora" |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, device_map="auto") |
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model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map="auto") |
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input_text = """Eu răspund la întrebări pe baza contextului. |
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Context: În anul 1600, Mihai Viteazul a realizat prima unire a Țărilor Române: Țara Românească, Transilvania și Moldova. Această unire a fost un moment important în istoria României. |
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Întrebare: În ce an a realizat Mihai Viteazul prima unire a Țărilor Române? |
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Răspuns: """ |
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input_ids = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate( |
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**input_ids, |
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max_new_tokens=100, |
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eos_token_id=[13] # 13 is the token ID for a newline character at the end of a non-empty line |
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) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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Note: Adding a space at the end of the prompt has been observed to significantly improve the model's output quality. |
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## Training Details and Evaluation |
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Please refer to the paper for details on the model's training and evaluation. |
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## Citation |
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**BibTeX:** |
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``` |
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@inproceedings{dima2024roqllama, |
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title={RoQLlama: A Lightweight Romanian Adapted Language Model}, |
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author={George-Andrei Dima and Andrei-Marius Avram and Cristian-George Crăciun and Dumitru-Clementin Cercel}, |
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booktitle={Findings of the Association for Computational Linguistics: EMNLP 2024} |
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year={2024}, |
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url={https://arxiv.org/abs/2410.04269}, |
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} |
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``` |
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**APA:** |
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Dima, G. A., Avram, A. M., Crăciun, C. G., & Cercel, D. C. (2024). RoQLlama: A lightweight Romanian adapted language model. In _Findings of the Association for Computational Linguistics: EMNLP 2024_. |
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