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README.md
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base_model: mistral-community/Mixtral-8x22B-v0.1
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tags:
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- generated_from_trainer
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model-index:
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- name: out
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results: []
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---
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[<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)
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<details><summary>See axolotl config</summary>
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- Transformers 4.40.0.dev0
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- Pytorch 2.2.2+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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base_model: mistral-community/Mixtral-8x22B-v0.1
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tags:
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- generated_from_trainer
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- axolotl
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model-index:
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- name: out
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results: []
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datasets:
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- cognitivecomputations/Dolphin-2.9
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- teknium/OpenHermes-2.5
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- m-a-p/CodeFeedback-Filtered-Instruction
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- cognitivecomputations/dolphin-coder
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- cognitivecomputations/samantha-data
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- HuggingFaceH4/ultrachat_200k
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- microsoft/orca-math-word-problems-200k
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- abacusai/SystemChat-1.1
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- Locutusque/function-calling-chatml
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- internlm/Agent-FLAN
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language:
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- en
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---
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# Dolphin 2.9 Mixtral 8x22b 🐬
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Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
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Discord: https://discord.gg/8fbBeC7ZGx
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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My appreciation for the sponsors of Dolphin 2.9:
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xH100 node
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This model is based on Dolphin-2.9-Mixtral-8x22b, and is Apache-2.0 licensed.
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The base model has 64k context, and the full-weight fine-tuning was with 4k sequence length.
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It took 1 week on 8xH100 provided by Crusoe Cloud
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This model was trained FFT on 50% parameters (targeted with [Laser Scanner](https://github.com/cognitivecomputations/laserRMT/blob/main/laser_scanner.py) by Fernando, David, Lucas, and Eric) , using ChatML prompt template format.
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example:
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```
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<|im_start|>system
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You are Dolphin, a helpful AI assistant.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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Dolphin-2.9 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
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Dolphin 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 with 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.
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Dolphin is licensed Apache 2.0. I grant permission for any use, including commercial, that falls within accordance with Apache-2.0 license. Dolphin was trained on data generated from GPT4, among other models.
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## Evals
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/vHDgd4gfEMftZ8cJP3mRf.png)
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## Training
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[<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)
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<details><summary>See axolotl config</summary>
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- Transformers 4.40.0.dev0
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- Pytorch 2.2.2+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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