--- --- # Model Card for Model Mirror <!-- Provide a quick summary of what the model is/does. [Optional] --> A bunch of interesting models found online, mostly on Civitai. # Table of Contents - [Model Card for Model Mirror](#model-card-for--model_id-) - [Table of Contents](#table-of-contents) - [Table of Contents](#table-of-contents-1) - [Model Details](#model-details) - [Model Description](#model-description) - [Uses](#uses) - [Direct Use](#direct-use) - [Downstream Use [Optional]](#downstream-use-optional) - [Out-of-Scope Use](#out-of-scope-use) - [Bias, Risks, and Limitations](#bias-risks-and-limitations) - [Recommendations](#recommendations) - [Training Details](#training-details) - [Training Data](#training-data) - [Training Procedure](#training-procedure) - [Preprocessing](#preprocessing) - [Speeds, Sizes, Times](#speeds-sizes-times) - [Evaluation](#evaluation) - [Testing Data, Factors & Metrics](#testing-data-factors--metrics) - [Testing Data](#testing-data) - [Factors](#factors) - [Metrics](#metrics) - [Results](#results) - [Model Examination](#model-examination) - [Environmental Impact](#environmental-impact) - [Technical Specifications [optional]](#technical-specifications-optional) - [Model Architecture and Objective](#model-architecture-and-objective) - [Compute Infrastructure](#compute-infrastructure) - [Hardware](#hardware) - [Software](#software) - [Citation](#citation) - [Glossary [optional]](#glossary-optional) - [More Information [optional]](#more-information-optional) - [Model Card Authors [optional]](#model-card-authors-optional) - [Model Card Contact](#model-card-contact) - [How to Get Started with the Model](#how-to-get-started-with-the-model) # Model Details ## Model Description <!-- Provide a longer summary of what this model is/does. --> A bunch of interesting models found online, mostly on Civitai. - **Developed by:** O, r, i, g, i, n, a, l, , C, r, e, a, t, o, r, s - **Shared by [Optional]:** M, i, r, r, o, r, i, n, g - **Model type:** Language model - **Language(s) (NLP):** en - **License:** wtfpl - **Parent Model:** More information needed - **Resources for more information:** More information needed # Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ## Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> <!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." --> ## Downstream Use [Optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> <!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." --> ## Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> <!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." --> # Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ## Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> # Training Details ## Training Data <!-- 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. --> More information on training data needed ## Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> ### Preprocessing More information needed ### Speeds, Sizes, Times <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> More information needed # Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ## Testing Data, Factors & Metrics ### Testing Data <!-- This should link to a Data Card if possible. --> More information needed ### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> More information needed ### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> More information needed ## Results More information needed # Model Examination More information needed # Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** More information needed - **Hours used:** More information needed - **Cloud Provider:** More information needed - **Compute Region:** More information needed - **Carbon Emitted:** too much! # Technical Specifications [optional] ## Model Architecture and Objective More information needed ## Compute Infrastructure More information needed ### Hardware More information needed ### Software More information needed # Citation <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> **BibTeX:** More information needed **APA:** More information needed # Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> More information needed # More Information [optional] !find models embeddings --type f --size -2 | while read a; do echo "https://huggingface.co/anonderpling/civitai_mirror/resolve/main/${a}"; echo " out=${a}"; rm "${a}"; done | tee aria2.in.txt !aria2 -x16 --split=16 -i aria2.in.txt # Model Card Authors [optional] <!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. --> More information needed # Model Card Contact n, o, b, o, d, y, , k, n, o, w, s, , t, h, e, , t, r, o, u, b, l, e, s, , I, ', v, e, , s, e, e, n, ,, , n, o, b, o, d, y, , k, n, o, w, s, , m, y, , s, o, r, r, o, w, # How to Get Started with the Model Use the code below to get started with the model. <details> <summary> Click to expand </summary> from transformers import ${model.config?.adapter_transformers?.model_class} model = ${model.config?.adapter_transformers?.model_class}.from_pretrained("${model.config?.adapter_transformers?.{model.id}}") model.load_adapter("Model Mirror", source="hf") </details>