---
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.

![img](./gianthydra.png)


## Model Details

### Model Description

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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](https://huggingface.co/ibivibiv)
- **Funded by:** [ibivibiv](https://huggingface.co/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](https://huggingface.co/AIDC-ai-business/Marcoroni-70B-v1)
[Aurora-Nights-70B-v1.0](https://huggingface.co/sophosympatheia/Aurora-Nights-70B-v1.0)
[strix-rufipes-70b](https://huggingface.co/ibivibiv/strix-rufipes-70b) <-- this one is mine :)  I'm a bit proud, sorry.
[ICBU-NPU/FashionGPT-70B-V1.1](https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1)


## Uses

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### 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

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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

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## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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#### Factors

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### Results

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#### Summary



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## Environmental Impact

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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]
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## Technical Specifications [optional]

### Model Architecture and Objective

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## Citation [optional]

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