---
library_name: transformers
tags:
- llama-factory
- merge
license: llama3
language:
- en
---

# Model Card for Model ID

This is a fine tune of a merged model using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b) as a base.
The following models were included in the merge:
* [Weyaxi/Einstein-v6.1-Llama3-8B](https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B)




## Model Details

### Model Description

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

- **Developed by:** [Gianni Sanrochman](https://x.com/Giannisanii)
- **Funded by:** [Merildo Sanrochman]
- **Model type:** [LLaMA-3](https://ai.meta.com/blog/meta-llama-3)
- **Language(s) (NLP):** [English]
- **License:** [llama3](https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE)
- **Finetuned from model:** [giannisan/dolphin-einstein-llama3-dare-ties](https://huggingface.co/giannisan/dolphin-einstein-llama3-dare-ties) using the PENNY dataset

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## 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

Use the code below 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

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

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

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## Evaluation

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### 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

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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:** [Nvidia RTX A100]
- **Hours used:** [2]
- **Cloud Provider:** [RunPod]
- **Compute Region:** [Europe]
- **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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**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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