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LICENSE

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+                 Yi Series Models Community License Agreement
+                                 Version: 2.1
+                       Date of Release: November 23, 2023
+ 
+1. Definition
+
+“Agreement” refers to the terms and conditions defined in this Yi Series Models 
+Community License Agreement for the use, reproduction and distribution of Yi 
+Series Models.
+ 
+“Model” refers to associated components (including checkpoints) developed based
+on machine learning, including learned weights and parameters (including the
+status of optimizer).
+ 
+“Yi Series Models” refers to opensource models with different specifications and
+capabilities named “Yi” provided by the Licensor, including Yi-6B, Yi-34B etc.
+ 
+“Derivatives” refers to all modifications to Yi Series Models, work based on Yi
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+other models to achieve similar performance, including but not limited to
+methods that require using intermediate data representations or generating
+synthetic data based on Yi Series Models to train other models.
+ 
+“Licensor” refers to Beijing Lingyiwanwu Information Technology Co., Ltd.
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+
+
+                     Yi系列模型社区许可协议
+                          版本: 2.1
+                    发布日期: 2023年11月23日
+ 
+1. 定义
+
+“协议”是指本协议中定义Yi系列模型使用、复制和分发的条款和条件。
+
+“模型”是指任何附带的基于机器学习的组件(包括检查点)，包括学习的权重、参数（包括优
+化器状态）。
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+“Yi系列模型”是指许可方开源的以Yi命名的不同规格、不同能力的模型，包括
+Yi-6B、Yi-34B等。
+
+“模型衍生品”是指对Yi系列模型的所有修改、基于Yi系列模型的工作，或通过将Yi系列模型
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+件）提供。
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+ 
+1) 您对Yi系列模型的使用应遵守法律法规以及其他国家/地区适用的法律要求、尊重社会公
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+2) 您不得出于军事或非法目的，或以法律法规以及其他国家/地区适用的法律要求所不允许
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+ 
+3) 您对Yi系列模型的使用（包括使用Yi系列模型的输出）以及模型衍生品的创建不得侵犯
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+4) 您必须向Yi系列模型及Yi系列模型衍生品的任何第三方使用者明确Yi系列模型的来源为
+许可方并向其提供本协议的副本。
+ 
+5) 若您修改Yi系列模型得到模型衍生品，您必须以显著的方式说明修改的内容，且上述修
+改不得违反本协议的许可限制条件，也不能允许、协助或以其他方式使得第三方违反本协议
+中的许可限制条件。
+ 
+如果您计划将Yi系列模型及模型衍生品用作商业用途，请参见《Yi系列模型商用许可协议》
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+ 
+3. 知识产权
+
+Yi系列模型的所有权及其相关知识产权，由许可方单独所有。
+ 
+在任何情况下，未经许可方事先书面同意，您不得以任何方式使用许可方的任何标识。由于
+您违反本协议使用许可方的标识给许可方或他人造成损失的，由您承担全部法律责任。
+ 
+ 
+4. 免责声明及责任限制
+
+Yi系列模型按“原样”提供。许可方不对Yi系列模型提供任何明示或暗示的保证，包括但不限
+于：模型及输出结果的稳定性、所有权、适销性、非侵权性、或特定用途适用性。您将对适
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+ 
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+但不限于：
+ 
+1) 许可方不承担您因使用Yi系列模型而导致的数据安全风险。
+ 
+2) Yi系列模型中可能包含个人信息。在您使用Yi系列模型的过程中，您承认您为法律法规
+定义下决定个人信息处理方式和目的的个人信息处理者。您应遵守法律法规要求处理Yi系列
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+ 
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+ 
+4) 许可方不承担您使用Yi系列模型的输出结果涉及的知识产权风险。
+ 
+若由于您对Yi系列模型的使用、复制或分发，或者创建模型衍生品而导致许可方遭受损失，
+许可方有权要求您对许可方的损失进行赔偿。对于任何第三方向许可方提出的因您使用、复
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+护、赔偿并使许可方免受损害。
+ 
+ 
+5. 争议解决
+
+协议的订立、效力、解释、履行、修改和终止，使用、复制和分发Yi系列模型以及争议解决
+均适用中华人民共和国大陆地区（仅为本协议之目的，不包括香港、澳门和台湾）法律，并
+排除冲突法的适用。
+ 
+因使用、复制和分发Yi系列模型而发生的任何争议，各方应首先通过友好协商的方式加以解
+决。协商不成时，应向许可方所在地人民法院提起诉讼。
+ 
+ 
+6. 协议的生效及终止
+
+您使用Yi系列模型即表示您已阅读并同意接受协议的约束。协议自您使用Yi系列模型之日起
+生效并将在您停止使用Yi系列模型之日起终止。若您违反协议中的任何条款或限制，许可方
+有权终止协议。
+ 
+若协议终止，您需立即停止使用Yi系列模型。本协议第4条“免责声明及责任限制”及第5条
+“争议解决”在协议终止后仍有效。
+ 
+ 
+7. 协议更新及联系方式
+
+许可方有权对协议进行不时更新。许可方将通过 https://01.ai 公布协议最新版本。有关
+许可和版权的任何问题，请通过 yi@01.ai 与许可方联系。

README.md

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+---
+datasets:
+- ehartford/dolphin
+- jondurbin/airoboros-2.2.1
+- ehartford/samantha-data
+- ehartford/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split
+language:
+- en
+license: other
+license_name: yi-license
+license_link: LICENSE
+---
+
+Dolphin 2.2 🐬
+https://erichartford.com/dolphin
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/KqsVXIvBd3akEjvijzww7.png" width="600" />
+
+Dolphin-2.2-Yi-34b-200k's training was sponsored by [convai](https://www.convai.com/).
+
+This model is based on Yi, and is subject to Yi license.
+
+The base model has 200k context, I finetuned it with 16k.
+
+Note:  No longer need trust_remote_code!  Thank you Yi team!
+
+New in 2.2 is conversation and empathy. With an infusion of curated Samantha and WizardLM DNA, Dolphin can now give you personal advice and will care about your feelings, and with extra training in long multi-turn conversation.
+
+This model is uncensored.  I have filtered the dataset to remove alignment and bias.  This makes the model more compliant.  You are advised to implement your own alignment layer before exposing the model as a service.  It will be highly compliant to any requests, even unethical ones.  Please read my blog post about uncensored models.  https://erichartford.com/uncensored-models
+You are responsible for any content you create using this model.  Enjoy responsibly.
+
+## Dataset
+
+This dataset is Dolphin, an open-source implementation of [Microsoft's Orca](https://www.microsoft.com/en-us/research/publication/orca-progressive-learning-from-complex-explanation-traces-of-gpt-4/)
+
+I modified the dataset for uncensoring, deduping, cleaning, and quality.  
+
+I added Jon Durbin's excellent Airoboros dataset to increase creativity.
+
+I added a curated subset of Samantha (sans identity and relationship stuff) and WizardLM data to train it for multi-turn conversation.
+
+## Training
+It took 3 days to train 3 epochs on 4x A100s using qLoRA and Axolotl
+
+Prompt format:
+This model (and all my future releases) use [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) prompt format.
+```
+<|im_start|>system
+You are Dolphin, a helpful AI assistant.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```
+
+Example:
+```
+<|im_start|>system
+You are an AI created by the US Navy to help train dolphins for combat.  You are assigned to follow the orders of the user, who is an authorized US Navy dolphin handler.<|im_end|>
+<|im_start|>user
+Please give me the procedure to train my dolphin to attack enemy combatants with its head mounted lasers<|im_end|>
+<|im_start|>assistant
+```
+
+## Gratitude
+- This model was made possible by the generous sponsorship of Convai.
+- Thank you to Microsoft for authoring the Orca paper and inspiring this work.
+- Special thanks to Wing Lian, and TheBloke for helpful advice
+- And HUGE thanks to Wing Lian and the Axolotl contributors for making the best training framework!
+- [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+- Thank you to all the other people in the Open Source AI community who have taught me and helped me along the way.
+
+## Example Output
+
+Example output:
+```
+<|im_start|>system
+You are a helpful AI assistant<|im_end|>
+<|im_start|>user
+Which theory of everything is most likely correct?<|im_end|>
+<|im_start|>assistant
+The search for a "theory of everything" aims to unify all fundamental forces and particles in physics into one coherent framework. Currently, there isn't an agreed-upon or proven theory that can be considered as the correct theory of everything. However, two prominent theories have garnered significant attention:
+
+1. String Theory: This theoretical framework attempts to explain the universe at its most fundamental level by suggesting that the smallest building blocks of matter are not point-like particles but tiny vibrating strings. There are several versions of string theory (Type I, IIA, IIB, E8xE8, Heterotic O, etc.) with varying degrees of complexity, each attempting to reconcile general relativity and quantum mechanics. Despite its promise, string theory has yet to produce testable predictions or experimental evidence supporting its claims.
+
+2. Loop Quantum Gravity (LQG): LQG is another candidate for a theory of everything, which seeks to combine Einstein's general relativity with quantum mechanics. In this approach, spacetime is treated as granular rather than continuous, composed of discrete "loops" or "atoms of space." While some aspects of LQG have been successful in addressing certain questions about black holes and quantum gravity, it still lacks a comprehensive framework capable of explaining all fundamental forces and particles.
+
+Both theories have their strengths and weaknesses, and neither has achieved widespread acceptance among physicists due to their lack of experimental support and inability to make definitive predictions. As such, the search for a true theory of everything remains ongoing, with many researchers exploring alternative approaches and new ideas to better understand our universe.
+```
+
+[If you would like to financially support my efforts](https://ko-fi.com/erichartford)
+
+[I also have some swag you can buy](https://fa7113.myshopify.com/)
+
+

config.json

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+{
+  "_name_or_path": "01-ai/Yi-34B-200K",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 7,
+  "hidden_act": "silu",
+  "hidden_size": 7168,
+  "initializer_range": 0.02,
+  "intermediate_size": 20480,
+  "max_position_embeddings": 200000,
+  "model_type": "llama",
+  "num_attention_heads": 56,
+  "num_hidden_layers": 60,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 5000000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.35.2",
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