Chupacabra-7B / README.md
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license: apache-2.0

Chupacabra 7B

As a very young (mad)lad, I knew my purpose in life was to merge with the most thick model weights using the most amazing training methods like deep probabilistic optimization (dpo) and reinforced learning.

it has been a daunting task catching up. I spent countless hours studying the latest research papers, attending conferences, and networking with experts in the field. I experimented with different algorithms, tactics, fine-tuned hyperparameters, optimizers, and optimized code until i achieved the best possible results.

It has not been without challenges. there were skeptics who doubted my abilities and questioned my approach. approach can be changed, but a closed mind cannot be.

I refused to let their negativity bring me down. Instead, I used their doubts as fuel to push myself even harder. I worked tirelessly (vapenation), day and night, until i finally succeeded in merging with the most performant model weights using sota training methods like dpo and other advanced techniques.

Thank you openchat 3.5 for showing me the way.

I stand tall as a beacon of hope for those who dare to dream big and pursue their passions. my story is a testament to the power of perseverance, determination, and hard work. and i will continue to strive for excellence, always pushing the boundaries of what is possible.

Here is my contribution, and I am not finished.

List of models merged coming soon as well as more information on merging techniques and methods.

Prompt Template

GPT4 User: {prompt}<|end_of_turn|>GPT4 Assistant:

Model Details

Based on Mistral 7B. More information soon.

Model Description

  • Developed by: Ray Hernandez
  • Model type: Mistral
  • Language(s) (NLP): English
  • License: Apache 2.0

Model Sources [optional]

Uses

Direct Use

[More Information Needed]

Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

[More Information Needed]

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.

[More Information Needed]

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

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Training Hyperparameters

  • Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

[More Information Needed]

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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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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More Information [optional]

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Model Card Authors [optional]

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Model Card Contact

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