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Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

  • Developed by: Prerna
  • Funded by [optional]: None
  • Shared by [optional]:
  • Model type: Text-to-text
  • Language(s) (NLP): English
  • License: Free to use
  • Finetuned from model [optional]: Google "t5small"

Model Sources [optional]

  • Repository: Google T5 small
  • Paper [optional]:
  • Demo [optional]:

Uses

Direct Use

Downstream Use [optional]

Out-of-Scope Use

Bias, Risks, and Limitations

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

github: Prerna-2055/Federated-Learning-for-LLMs-with-Model-Compression

Training Details

Training Data

HealthcareMagic ChatDoctor-en

Training Procedure

Preprocessing [optional]

Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

Evaluation

Testing Data, Factors & Metrics

Testing Data

Factors

Metrics

Results

Summary

Model Examination [optional]

Environmental Impact

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

  • Hardware Type: [More Information Needed]
  • Hours used: [More Information Needed]
  • Cloud Provider: [More Information Needed]
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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Model size
60.5M params
Tensor type
F32
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Paper for Prerna2055/T5_FL_Base_Model_without_LoRA