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Llama3.1-70B-GeoGPT License Agreement ADDED
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+ Llama3.1-70B-GeoGPT License Agreement
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+
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+ Llama3.1-70B-GeoGPT Release Date: 27 April, 2025
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+
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+ This Agreement applies to any use, reproduction, modification, or distribution of any Llama3.1-70B-GeoGPT Materials by You, regardless of the source You obtained a copy of such Materials. By using, modifying or distributing any portion or element of the Llama3.1-70B-GeoGPT Materials, You will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately, and you agree to be bound by this Agreement.
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+
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+ 1. Definitions
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+ 1.1 "Agreement" shall mean the terms and conditions for use, reproduction, distribution and modification of the Llama3.1-70B-GeoGPT Materials set forth herein.
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+ 1.2 "We" or "Us" shall mean Zhejiang Lab.
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+ 1.3 "You" or "Your" shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or making use of the Materials for any purpose and in any field of use.
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+ 1.4 "Llama3.1-70B-GeoGPT" shall mean the large language model created, trained, fine-tuned, and distributed by Us, based on the Llama3.1-70B foundation model.
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+ 1.5 "Materials" shall mean, collectively, the trained model weights, parameters (including optimizer states) and other elements of Llama3.1-70B-GeoGPT made available under this Agreement.
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+ 1.6 "Derivative Works" shall mean any modified version of the Materials, or any other work derived from the Materials.
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+ 1.7 "Noncommercial Purposes" shall mean any use that is not primarily intended for or directed toward commercial advantage or monetary compensation.
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+
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+ 2.Grant of Rights
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+ 2.1 You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Zhejiang Lab's intellectual property or other rights owned by Zhejiang Lab embodied in the Materials to use, reproduce, distribute, copy, create Derivative Works of, and make modifications to the Materials.
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+
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+ 3. Redistribution and Use
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+ 3.1 You may reproduce and distribute copies of the Materials or Derivative Works thereof in any medium, with or without modifications, provided You meet the following conditions:
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+ a. You shall provide a copy of this Agreement to any other recipients of the Materials or Derivative Works.
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+ b. You shall cause any Derivative Works to carry prominent notices stating that You modified the Materials.
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+ c. You shall retain in all copies of the Materials that You distribute the following attribution notice within a "Notice" text file distributed as a part of such copies: "Llama3.1-70B-GeoGPT is licensed under the Llama3.1-70B-GeoGPT License Agreement, Copyright © Zhejiang Lab. All Rights Reserved."
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+ d. You shall retain and reproduce any disclaimer of warranty or limitation of liability contained in the original Materials. Any redistribution of the Materials or Derivative Works must include this disclaimer in its entirety.
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+ 3.2 You may add Your own copyright statement to Your Derivative Works and may provide additional or different license terms and conditions for the use, reproduction, or distribution of Derivative Works, provided Your use, reproduction, and distribution of the Materials and/or the Derivative Works otherwise complies with the terms and conditions of this Agreement.
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+
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+ 4. Restrictions
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+ 4.1 The Materials may be subject to export controls or restrictions in China, the United States or other countries or regions. Even though the materials contain no technology subject to Chinese export controls, You shall comply with relevant applicable laws and regulations in your use of the Materials.
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+ 4.2 You shall adhere to the Code of Conduct which is incorporated by reference into this Agreement.
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+ 4.3 You shall use Materials for NONCOMMERCIAL PURPOSES ONLY.
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+
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+ 5. Intellectual Property
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+ 5.1 No trademark licenses are granted to use the trade names, trademarks, service marks, or product names of Us, except as required to fulfill notice requirements under this Agreement or as required for reasonable and customary use in describing and redistributing the Materials.
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+ 5.2 IMPORTANT NOTICE: Subject to Meta's ownership of "Llama", this Agreement shall not be construed as granting You any license to use the name or trademark of "Llama" by Us. Your use of "Llama" shall comply with the META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT.
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+ 5.3 We retain ownership of all intellectual property rights in and to the Materials and derivatives made by or for Us. Conditioned upon compliance with the terms and conditions of this Agreement, with respect to any Derivative Works and modifications of the Materials that are made by You, You are and will be the owner of such Derivative Works and modifications.
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+ 5.4 If You institute litigation or other proceedings against Us (including a cross-claim or counterclaim in a lawsuit) alleging that the Materials, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by You, then any licenses granted to You under this Agreement shall terminate as of the date such litigation or claim is filed or instituted.
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+
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+ 6. Disclaimer of Warranty
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+ 6.1 UNLESS REQUIRED BY APPLICABLE LAW, THE MATERIALS ARE PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES OF ANY KIND, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE MATERIALS.
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+ 6.2 We are not obligated to support, update, provide training for, or develop any further version of the Materials or to grant any license thereto.
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+
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+ 7. Limitation of Liability
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+ 7.1IN NO EVENT SHALL WE BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF WE HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
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+ 7.2 You will defend, indemnify and hold harmless Us from and against any claim by any third party arising out of or related to Your use or distribution of the Materials.
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+
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+ 8. Term and Termination
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+ 8.1 The term of this Agreement shall commence upon Your acceptance of this Agreement or access to the Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein.
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+ 8.2 We may terminate this Agreement if You are in breach of any term or condition of this Agreement. Upon termination of this Agreement, You shall delete and cease use of the Materials. Sections 5.1、5.2、5.4、6、7 and 9 shall survive the termination of this Agreement.
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+
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+ 9. Governing Law and Jurisdiction
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+ 9.1 This Agreement, and any disputes arising from or related to it, shall be governed and construed under the laws of the People's Republic of China. The United Nations Convention on Contracts for the International Sale of Goods (CISG) does not apply to this Agreement.
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+ 9.2 Any dispute from or related to this Agreement shall be under the exclusive jurisdiction of the People's Court of Yuhang District, Hangzhou City, Zhejiang Province, People's Republic of China. This choice of jurisdiction complies with relevant international treaties and local laws of the chosen jurisdiction. For cross-border disputes or cases with foreign elements, the parties may select any court with competent jurisdiction, including those in other countries or regions, by written agreement, provided it does not violate Chinese law's exclusive jurisdiction provisions and complies with relevant international treaties and local laws of the chosen jurisdiction.
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+
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+ 10. Severability
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+ 10.1 If any provision of the Agreement is held to be or becomes invalid, illegal, or unenforceable under applicable law, the validity, legality, or enforceability of the remaining provisions shall not be affected or impaired thereby.
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+
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+ 11.META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT
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+ 11.1 Llama3.1-70B-GeoGPT is based on the Llama3.1-70B foundation model. Subject to Meta's ownership of Llama, Your use of Llama3.1 shall comply with the META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT (https://huggingface.co/meta-llama/Llama-3.1-70B/blob/main/LICENSE, a copy of this license). You shall also ensure that your use of Llama3.1-70B-GeoGPT does not violate the META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT.
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: other
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+ license_name: geogpt
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+ license_link: >-
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+ https://huggingface.co/GeoGPT-Research-Project/Llama3.1-70B-GeoGPT/blob/main/Llama3.1-70B-GeoGPT%20License%20Agreement
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+ pipeline_tag: text-generation
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+ base_model:
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+ - meta-llama/Llama-3.1-70B
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+ ---
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+
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+ # Llama3.1-70B-GeoGPT
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+ <!-- markdownlint-disable first-line-h1 -->
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+ <!-- markdownlint-disable html -->
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+ <!-- markdownlint-disable no-duplicate-header -->
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+
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+
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+ <div align="center">
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+ <img src="https://huggingface.co/GeoGPT-Research-Project/Llama3.1-70B-GeoGPT/resolve/main/dynamic_geogpt.gif" width="99%" alt="GeoGPT" />
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+ </div>
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+ <hr>
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+ <div align="center" style="line-height: 1;">
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+ <a href="https://geogpt.zero2x.org/" target="_blank" style="margin: 2px;">
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+ <img alt="Homepage" src="https://img.shields.io/badge/🌐%20Homepage-GeoGPT%20-536af5" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://github.com/GeoGPT-Research-Project/GeoGPT" target="_blank" style="margin: 2px;">
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+ <img alt="Github" src="https://img.shields.io/badge/🐙%20Github-GeoGPT%20-ffc107" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://modelscope.cn/profile/GeoGPT" target="_blank" style="margin: 2px;">
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+ <img alt="ModelScope" src="https://img.shields.io/badge/🤖%20ModelScope-GeoGPT%20-536af5" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ </div>
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+
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+ <div align="center" style="line-height: 1;">
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+ <a href="https://www.linkedin.com/company/zhejianglab/posts/?feedView=all&viewAsMember=true" target="_blank" style="margin: 2px;">
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+ <img alt="LinkedIn" src="https://img.shields.io/badge/💬%20LinkedIn-GeoGPT-brightgreen?logo=Linkedin&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://huggingface.co/GeoGPT-Research-Project/Llama3.1-70B-GeoGPT/blob/main/Llama3.1-70B-GeoGPT%20License%20Agreement" style="margin: 2px;">
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+ <img alt="License" src="https://img.shields.io/badge/📑%20License-Customized License-f5de53" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <br>
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+ </div>
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+
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+ ## 1. Introduction
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+
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+ The GeoGPT collection of models are large language models for advancing geosciences research. Built upon state-of-the-art foundation models, GeoGPT models offer enhanced capabilities in specialized areas of geoscience through a series of post-training processes, including CPT, SFT, and DPO.
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+
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+ GeoGPT embraces the open science principles of collaboration, sharing, and co-construction, with a strong commitment to supporting the global geosciences research community. To this end, we have openly released three models:
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+
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+ - [Llama3.1-70B-GeoGPT](https://huggingface.co/GeoGPT-Research-Project/Llama3.1-70B-GeoGPT): a large language model based on the foundation of Llama3.1-70B.
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+ - [Qwen2.5-72B-GeoGPT](https://huggingface.co/GeoGPT-Research-Project/Qwen2.5-72B-GeoGPT): a large language model based on the foundation of Qwen2.5-72B.
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+ - [GeoGPT-R1-Preview](https://huggingface.co/GeoGPT-Research-Project/GeoGPT-R1-Preview): a large language reasoning model based on the foundation of Qwen2.5-72B, featuring remarkable reasoning capabilities in answering geoscience questions.
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+
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+ Our goal is to provide valuable AI tools to scientists, researchers, and professionals engaged in geoscience research worldwide.
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+
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+
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+ ## 2. Model Information
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+
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+ ### Training Data
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+
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+ GeoGPT respects intellectual property rights and highly values the copyright and proper attribution of authors, researchers, and publishers. To uphold the credibility and integrity of scientific research, GeoGPT relies solely on authoritative and impartial data from trusted sources. The data utilized in training GeoGPT is derived from the following sources:
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+
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+ - A geoscience-specific subset of [CommonCrawl](https://commoncrawl.org/). CommonCrawl is a publicly-available collection of web pages curated by crawling open websites. It is widely-leveraged to train leading large language models. We apply data mining algorithms to extract geoscience-related content from the raw CommonCrawl dataset. For more details, see [GeoGPT Training Data from Geoscience Subset of CommonCrawl](https://github.com/GeoGPT-Research-Project/GeoGPT/blob/main/GeoGPT%20Training%20Data%20from%20Geoscience%20Subset%20of%20CommonCrawl.md). The metadata information is available on [Hugging Face](https://huggingface.co/datasets/GeoGPT-Research-Project/GeoGPT_Training_Data_from_Geoscience_Subset_of_CommonCrawl).
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+
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+
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+ - Open access publications licensed under CC BY or CC BY-NC. Through meticulous license filtering, we have curated approximately 280,000 papers from 15 publishers and 182 journals. The full list is described at [GeoGPT Training Data from Open Access Papers](https://github.com/GeoGPT-Research-Project/GeoGPT/blob/main/GeoGPT%20Training%20Data%20from%20Open%20Access%20Papers.md).
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+
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+ ### Training Process
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+
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+ The GeoGPT models are trained in three stages:
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+
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+ - Continual Pre-training (CPT): This stage utilizes a diverse set of geoscience-related corpora to obtain a solid specialized model for geoscience.
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+
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+ - Supervised Fine-tuning (SFT): This stage enhances the model’s ability to follow geoscience-specific instructions by incorporating QA pairs labeled by geoscientists, along with those generated from the training corpus in CPT stage.
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+
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+ - Human Preference Alignment: This stage uses the Direct Preference Optimization (DPO) with preference data labeled by large language models to align model's responses with human expectations and preferences.
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+
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+
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+ ## 3. Model Downloads
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+
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+ GeoGPT models can be downloaded from [Hugging Face](https://huggingface.co/GeoGPT-Research-Project) and [ModelScope](https://modelscope.cn/profile/GeoGPT).
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+
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+ <div align="center">
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+
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+ | **Model** | **Total Params** |**Supported Language** | **Base Model** | **Hugging Face** |**ModelScope** |
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+ | :------------: | :------------: | :------------: | :------------: |:------------: | :------------: |
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+ | Llama3.1-70B-GeoGPT | 70B | Primary English and Chinese | [Llama3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B) | [🤗 Hugging Face](https://huggingface.co/GeoGPT-Research-Project/Llama3.1-70B-GeoGPT) | [🤖 ModelScope](https://modelscope.cn/models/GeoGPT/Llama3.1-70B-GeoGPT) |
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+
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+ </div>
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+
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+ ## 4. Quickstart
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+
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+ ### Llama3.1-70B-GeoGPT
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+ To load the Llama3.1-70B-GeoGPT model with Transformers, use the following snippet:
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+
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_name = "GeoGPT-Research-Project/Llama3.1-70B-GeoGPT"
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_name,
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+ torch_dtype="auto",
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ prompt = "What are the main components of granite?"
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+ messages = [
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+ {"role": "system", "content": "You are a helpful assistant named GeoGPT."},
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+ {"role": "user", "content": prompt}
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+ ]
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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+
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+ generated_ids = model.generate(
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+ **model_inputs,
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+ max_new_tokens=4096
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+ )
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+ generated_ids = [
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+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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+ ]
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+
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+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+ ```
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+
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+
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+ ## 5. License and Uses
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+ **License**:Llama3.1-70B-GeoGPT is licensed under the [Llama3.1-70B-GeoGPT License Agreement](https://github.com/GeoGPT-Research-Project/GeoGPT/blob/main/Llama3.1-70B-GeoGPT%20License%20Agreement). Please note that:
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+
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+ - Llama3.1-70B-GeoGPT is trained on the foundation of Llama3.1-70B. Your use of Llama3.1-70B-GeoGPT shall therefore comply with the [LLAMA 3.1 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Llama-3.1-70B/blob/main/LICENSE).
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+
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+
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+ **Primary intended use**:The primary use of GeoGPT models is to support geoscience research, providing geoscientists with innovative tools and capabilities enhanced by large language models. It is specifically designed for non-commercial research and educational purposes.
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+
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+ **Out-of-scope use**:GeoGPT models are not intended for use in any manner that violates applicable laws or regulations, nor for any activities prohibited by the license agreement. Additionally, it is not intended for use in languages other than those explicitly supported, as outlined in this model card.
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+
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+
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+ ## 6. Ethical Considerations and Limitations
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+ **Values**: GeoGPT promotes the open science principles of collaboration, sharing, and co-construction. By facilitating collaboration across disciplines and geographical boundaries, GeoGPT seeks to empower experts and innovators with the tools they need to address complex global challenges. We welcome individuals from various backgrounds, experiences, and perspectives to join us in exploring the opportunities and challenges brought by AI and large-scale models.
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+
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+ **Limitations**: Similar to other language models, the GeoGPT models may occasionally behave in ways that pose potential risks. These models might generate inaccurate, biased, or otherwise objectionable responses to user inputs. Therefore, before deploying applications built on GeoGPT models, developers should conduct thorough safety testing and implement measures to mitigate risks specific to their intended use cases, considering cultural and linguistic contexts.
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+
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+
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+ ## 7. Contact
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+ If you have any questions, please raise an issue or contact us at [[email protected]]([email protected]).
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+ "vocab_size": 128256
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+ }
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1780
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1788
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1814
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1815
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1817
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1820
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1823
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1825
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1828
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1830
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1831
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1833
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1834
+ },
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1836
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1838
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1852
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+ },
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1884
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+ "lstrip": false,
1886
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1887
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1888
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1890
+ },
1891
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1892
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1893
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1894
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1895
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1896
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1897
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1898
+ },
1899
+ "128237": {
1900
+ "content": "<|reserved_special_token_229|>",
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+ "lstrip": false,
1902
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1903
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1904
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1905
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1906
+ },
1907
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1908
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+ "lstrip": false,
1910
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1911
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1912
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1913
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1914
+ },
1915
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1916
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1918
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1919
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1920
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1921
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1922
+ },
1923
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1924
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1925
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1926
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1927
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1928
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1929
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1930
+ },
1931
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1932
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1933
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1934
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1935
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1936
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1937
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1938
+ },
1939
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1940
+ "content": "<|reserved_special_token_234|>",
1941
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1942
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1943
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1944
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1945
+ "special": true
1946
+ },
1947
+ "128243": {
1948
+ "content": "<|reserved_special_token_235|>",
1949
+ "lstrip": false,
1950
+ "normalized": false,
1951
+ "rstrip": false,
1952
+ "single_word": false,
1953
+ "special": true
1954
+ },
1955
+ "128244": {
1956
+ "content": "<|reserved_special_token_236|>",
1957
+ "lstrip": false,
1958
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1959
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1960
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1961
+ "special": true
1962
+ },
1963
+ "128245": {
1964
+ "content": "<|reserved_special_token_237|>",
1965
+ "lstrip": false,
1966
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1967
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1968
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1969
+ "special": true
1970
+ },
1971
+ "128246": {
1972
+ "content": "<|reserved_special_token_238|>",
1973
+ "lstrip": false,
1974
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1975
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1976
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1977
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1978
+ },
1979
+ "128247": {
1980
+ "content": "<|reserved_special_token_239|>",
1981
+ "lstrip": false,
1982
+ "normalized": false,
1983
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1984
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1985
+ "special": true
1986
+ },
1987
+ "128248": {
1988
+ "content": "<|reserved_special_token_240|>",
1989
+ "lstrip": false,
1990
+ "normalized": false,
1991
+ "rstrip": false,
1992
+ "single_word": false,
1993
+ "special": true
1994
+ },
1995
+ "128249": {
1996
+ "content": "<|reserved_special_token_241|>",
1997
+ "lstrip": false,
1998
+ "normalized": false,
1999
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2000
+ "single_word": false,
2001
+ "special": true
2002
+ },
2003
+ "128250": {
2004
+ "content": "<|reserved_special_token_242|>",
2005
+ "lstrip": false,
2006
+ "normalized": false,
2007
+ "rstrip": false,
2008
+ "single_word": false,
2009
+ "special": true
2010
+ },
2011
+ "128251": {
2012
+ "content": "<|reserved_special_token_243|>",
2013
+ "lstrip": false,
2014
+ "normalized": false,
2015
+ "rstrip": false,
2016
+ "single_word": false,
2017
+ "special": true
2018
+ },
2019
+ "128252": {
2020
+ "content": "<|reserved_special_token_244|>",
2021
+ "lstrip": false,
2022
+ "normalized": false,
2023
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2024
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2025
+ "special": true
2026
+ },
2027
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2028
+ "content": "<|reserved_special_token_245|>",
2029
+ "lstrip": false,
2030
+ "normalized": false,
2031
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2032
+ "single_word": false,
2033
+ "special": true
2034
+ },
2035
+ "128254": {
2036
+ "content": "<|reserved_special_token_246|>",
2037
+ "lstrip": false,
2038
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2039
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2040
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2041
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2042
+ },
2043
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2044
+ "content": "<|reserved_special_token_247|>",
2045
+ "lstrip": false,
2046
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2047
+ "rstrip": false,
2048
+ "single_word": false,
2049
+ "special": true
2050
+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 131072,
2061
+ "pad_token": "<|eot_id|>",
2062
+ "tokenizer_class": "PreTrainedTokenizerFast"
2063
+ }