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--- |
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license: cc |
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language: |
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- fa |
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- en |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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inference: false |
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metrics: |
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- bleu |
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- comet |
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- accuracy |
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- perplexity |
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- spearmanr |
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pipeline_tag: text-generation |
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co2_eq_emissions: |
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emissions: 232380 |
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--- |
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<img src="PersianMind.jpg" alt="PersianMind logo" width=200/> |
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# PersianMind |
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PersianMind is a a cross-lingual Persian-English large language model. |
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### Model Description |
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- **Developed by:** [Pedram Rostami](mailto:[email protected]), [Ali Salemi](mailto:[email protected]), and [Mohammad Javad Dousti](mailto:[email protected]) |
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- **Model type:** Language model |
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- **Languages:** English and Persian |
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- **License:** [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) |
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## How to Get Started with the Model |
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Use the code below to get started with the model. Note that you need to install `sentencepiece` and `accelerate` libraries to run this code. |
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```python |
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from transformers import LlamaTokenizer, LlamaForCausalLM |
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import torch |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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model = LlamaForCausalLM.from_pretrained( |
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"universitytehran/PersianMind-v1.0", |
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torch_dtype=torch.bfloat16, |
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low_cpu_mem_usage=True, |
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device_map={"": device}, |
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) |
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tokenizer = LlamaTokenizer.from_pretrained( |
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"universitytehran/PersianMind-v1.0", |
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) |
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TEMPLATE = "{context}\nYou: {prompt}\nPersianMind: " |
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CONTEXT = "This is a conversation with PersianMind. It is an artificial intelligence model designed by a team of " \ |
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"NLP experts at the University of Tehran to help you with various tasks such as answering questions, " \ |
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"providing recommendations, and helping with decision making. You can ask it anything you want and " \ |
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"it will do its best to give you accurate and relevant information." |
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PROMPT = "در مورد هوش مصنوعی توضیح بده." |
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model_input = TEMPLATE.format(context=CONTEXT, prompt=PROMPT) |
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input_tokens = tokenizer(model_input, return_tensors="pt") |
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input_tokens = input_tokens.to(device) |
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generate_ids = model.generate(**input_tokens, max_new_tokens=512, do_sample=False, repetition_penalty=1.1) |
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model_output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] |
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model_output = model_output.replace(model_input, "") |
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print(model_output) |
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``` |
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## License |
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PersianMind is subject to Meta's [LLaMa2 Community License](https://raw.githubusercontent.com/facebookresearch/llama/main/LICENSE). |
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It is further licensed under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/), which allows non-commercial use of the model. |
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Commercial use of this model requires written agreement which must be obtained from the copyright holders who are listed as developers in this page. |
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If you suspect any violations, please reach out to us. |
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## Citation |
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If you find the following model helpful, please ensure to cite the following paper. |
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**BibTeX:** |
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```bibtex |
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@article{persianmind, |
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title={{PersianMind: A Cross-Lingual Persian-English Large Language Model}}, |
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author={Rostami, Pedram and Salemi, Ali and Dousti, Mohammad Javad}, |
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journal={arXiv preprint}, |
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year={2024} |
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} |
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``` |
