Create README.md

README.md

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