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README.md
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tags:
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- generated_from_trainer
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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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</details><br>
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# qwen-out
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3931
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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license: other
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base_model: Qwen/Qwen1.5-110B
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tags:
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- generated_from_trainer
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- axolotl
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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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- microsoft/orca-math-word-problems-200k
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- Locutusque/function-calling-chatml
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- internlm/Agent-FLAN
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---
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# Dolphin 2.9.1 Qwen 110b 🐬
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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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Our appreciation for the sponsors of Dolphin 2.9.1:
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xH100 node
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This model is based on Qwen1.5-110B, and is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)
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The base model has 32k context, and the full-weight fine-tuning was with 8k sequence length.
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This model was trained FFT on parameters selected by [Laser Scanner](https://github.com/cognitivecomputations/laserRMT/blob/main/laser_scanner.py), 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-2.9.1 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. We 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 according to Meta's Llama license. We grant permission for any use, including commercial, that falls within accordance with Meta's Llama-3 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/U86Zu-MzLq4rECJRAAvgq.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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</details><br>
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## Training procedure
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### Training hyperparameters
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