初始化项目，由ModelHub XC社区提供模型

Model: Fsoft-AIC/XMAiNframe-instruct-7b
Source: Original Platform

README.md

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+---
+license: mit
+---
+
+<p align="center">
+  <img src="./asset/XMAiNframe.png"  width="560px" alt="logo">
+</p>
+
+<div align="center">
+  
+# XMAiNframe: A Large Language Model for Mainframe Modernization
+</div>
+
+## Introduction
+
+We are introducing **XMAiNframe**, a state-of-the-art large language model (LLM) specifically designed with knowledge of mainframe legacy systems and COBOL codebases. XMAiNframe is built on top of DeepSeek-Coder 7B and is available with 7B and 10.5B parameters.
+Additionally, we present [MainframeBench](https://huggingface.co/datasets/Fsoft-AIC/MainframeBench), a comprehensive benchmark for assessing mainframe knowledge, including multiple-choice questions, question answering, and COBOL code summarization. Our empirical evaluations demonstrate that XMAiNframe consistently outperforms existing state-of-the-art LLMs across these tasks. Specifically, XMAiNframe achieves 30% higher accuracy than DeepSeek-Coder on multiple-choice questions, doubles the BLEU score of Mixtral-Instruct 8x7B on question answering, and scores six times higher than GPT-3.5 on COBOL summarization. Our work highlights the potential of XMAiNframe to drive significant advancements in managing and modernizing legacy systems, thereby enhancing productivity and saving time for software developers.
+
+
+## Model Versions
+
+We release XMAiNframe with 7B and 10.5B parameters, including base and instruct models, to the public. XMAiNframe 10.5B is expanded from DeepSeek-Coder 7B by the depth up-scaling method without introducing additional modules or dynamic expert selection methods.
+
+<div align="center">
+
+|            **Model**            |      **Download**  |
+| :-----------------------------: |  :----------------------------------------------------------: |
+|   XMAiNframe-base-7b         | [🤗 HuggingFace](https://https://huggingface.co/Fsoft-AIC/XMAiNframe-base-7b/) |
+| XMAiNframe-instruct-7b    | [🤗 HuggingFace](https://huggingface.co/Fsoft-AIC/XMAiNframe-instruct-7b) |
+|     XMAiNframe-base-10.5b     |       [🤗 HuggingFace](https://huggingface.co/Fsoft-AIC/XMAiNframe-base-10.5b) |
+|   XMAiNframe-instruct-10.5b   |   [🤗 HuggingFace](https://huggingface.co/Fsoft-AIC/XMAiNframe-instruct-10.5b) |
+
+</div>
+
+
+## Quickstart
+
+Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
+
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/XMAiNframe-instruct-7b")
+model = AutoModelForCausalLM.from_pretrained("Fsoft-AIC/XMAiNframe-instruct-7b")
+messages=[
+    {'from':'system', 'value': "You are a helpful assistant"},
+    {'from': 'human', 'value': 'What is the future of Mainframe?'}
+]
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+ 
+outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
+print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
+```
+
+## Additional Information
+### Other Resources:
+- Github: https://github.com/FSoft-AI4Code/XMainframe
+- Paper: https://arxiv.org/abs/2408.04660
+
+
+### License
+[MIT License](LICENSE)
+
+### Citation Information
+More details can be found in our [paper](https://arxiv.org/abs/2408.04660). 
+
+If you're using XMAiNframe, please cite using this BibTeX:
+```
+@misc{dau2024xmainframelargelanguagemodel,
+      title={XMainframe: A Large Language Model for Mainframe Modernization}, 
+      author={Anh T. V. Dau and Hieu Trung Dao and Anh Tuan Nguyen and Hieu Trung Tran and Phong X. Nguyen and Nghi D. Q. Bui},
+      year={2024},
+      eprint={2408.04660},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2408.04660}, 
+}
+```
+
+# Contact us
+If you have any questions, comments or suggestions, please do not hesitate to contact us.
+- Website: [fpt-aicenter](https://www.fpt-aicenter.com/ai-residency/)
+- Email: support.ailab@fpt.com