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--- |
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license: creativeml-openrail-m |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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For llama-anon it is llama2 license |
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## Model Details |
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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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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** nRuaif |
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- **Model type:** large language model |
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- **License:** |
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- **Finetuned from model [optional]:** Llama-13B |
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### Model Sources [optional] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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The model uses Fastchat/ShareGPT format. |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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This model is finetuned for normal and erotic roleplay while can still an assistant. (Might not be a helpfull one through) |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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Do anything you want. I don't care |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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Model might have bias to NSFW due to the large % of NSFW data in the training set. |
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## Training Details |
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### Training Data |
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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3000 convos with 4090 cut off len. |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Training Hyperparameters |
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- **Training regime:** BF16, QLoRA, constant LR 5e-5 <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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### Compute Infrastructure |
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The model is trained on 1 A100 for 2 hours on runpod. |
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