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Nymbo/
Model_Repo_Template

Name: Model_Repo_Template
Availability: InStock

generic

text-to-image

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Text To Image repository template

This is a template repository for text to image to support generic inference with Hugging Face Hub generic Inference API. There are two required steps

Specify the requirements by defining a requirements.txt file.
Implement the pipeline.py __init__ and __call__ methods. These methods are called by the Inference API. The __init__ method should load the model and preload all the elements needed for inference (model, processors, tokenizers, etc.). This is only called once. The __call__ method performs the actual inference. Make sure to follow the same input/output specifications defined in the template for the pipeline to work.

Example repos

https://huggingface.co/osanseviero/BigGAN-deep-128/blob/main/pipeline.py

How to start

First create a repo in https://hf.co/new. Then clone this template and push it to your repo.

git clone https://huggingface.co/templates/text-to-image
cd text-to-image
git remote set-url origin https://huggingface.co/Nymbo/Model_Repo_Template
git push --force

For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1

Doc / guide: https://huggingface.co/docs/hub/model-cards

Model Card for {{ model_id | default("Model ID", true) }}

Model Details

Model Description

Developed by: {{ developers | default("[More Information Needed]", true)}}
Funded by [optional]: {{ funded_by | default("[More Information Needed]", true)}}
Shared by [optional]: {{ shared_by | default("[More Information Needed]", true)}}
Model type: {{ model_type | default("[More Information Needed]", true)}}
Language(s) (NLP): {{ language | default("[More Information Needed]", true)}}
License: {{ license | default("[More Information Needed]", true)}}
Finetuned from model [optional]: {{ base_model | default("[More Information Needed]", true)}}

Model Sources [optional]

Repository: {{ repo | default("[More Information Needed]", true)}}
Paper [optional]: {{ paper | default("[More Information Needed]", true)}}
Demo [optional]: {{ demo | default("[More Information Needed]", true)}}

Uses

Direct Use

Downstream Use [optional]

Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

{{ bias_recommendations | default("Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.", true)}}

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

Training Procedure

Preprocessing [optional]

Training Hyperparameters

Training regime: {{ training_regime | default("[More Information Needed]", true)}}

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

Factors

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Metrics

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Results

Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Hardware Type: {{ hardware_type | default("[More Information Needed]", true)}}
Hours used: {{ hours_used | default("[More Information Needed]", true)}}
Cloud Provider: {{ cloud_provider | default("[More Information Needed]", true)}}
Compute Region: {{ cloud_region | default("[More Information Needed]", true)}}
Carbon Emitted: {{ co2_emitted | default("[More Information Needed]", true)}}

Technical Specifications [optional]

Model Architecture and Objective

Compute Infrastructure

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Hardware

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Software

Citation [optional]

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APA:

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Nymbo/Model_Repo_Template