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metadata
library_name: transformers
tags:
  - moe
  - moerge
license: llama2
language:
  - en

Model Card for Giant Hydra 240B

Yes, you read that correctly, this is a 4x70b MOE model with ~240B parameters. I doubt there is any way that I will have the benchmarks run here anytime soon to be on the leaderboard but I am looking into renting time on runpod to get the scores myself and put them here.

This model should cover multiple different disciplines and behaviors well as I tried to use and gate correctly a wide set of models including one I fine tuned myself.

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Model Details

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: ibivibiv
  • Funded by: ibivibiv <-- right out of my poor pocket lol
  • Model type: MOE
  • Language(s) (NLP): English
  • License: Apache 2
  • Finetuned from model: see model sources below for list of models used in the MOE

Model Sources

I use the following 4 models to create an MOE that should cover multiple disciplines and do it well. I will most likely (if I can afford to do it), try this out and if I find that it is working I will make another variation.

Marcoroni-70B-v1 Aurora-Nights-70B-v1.0 strix-rufipes-70b <-- this one is mine :) I'm a bit proud, sorry. ICBU-NPU/FashionGPT-70B-V1.1

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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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.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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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: [More Information Needed]
  • Hours used: [More Information Needed]
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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]

BibTeX:

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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