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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.
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- **Developed by: kshabana
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- **Funded by no one
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- **Shared by kshabana
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- **Model type: safetensors and gguf
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- **Language(s) Arabic and English
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- **License:**
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- **Finetuned from model [llama3.1]
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### Model Sources []
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meta-llama/Meta-Llama-3.1-8B-Instruct
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- **Repository:**
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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[More Information Needed]
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### Recommendations
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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- arbml/alpaca_arabic
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# INTRO
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we are happy to announce that we are starting our goat model family
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# Model Card for Model ID
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this is a finetune model of llama3.1 that can perform well and we improved the generatal knoledge and and it can speak bunch of languages like arabic and english.
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- **Developed by: kshabana
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- **Funded by no one
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- **Shared by kshabana
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- **Model type: safetensors and gguf
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- **Language(s) Arabic and English
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- **License:** Apache2.0
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- **Finetuned from model [llama3.1-instruct]
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### Model Sources []
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https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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- **Dataset Repository:**
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https://huggingface.co/datasets/arbml/alpaca_arabic
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## Uses
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this model can be used for combanys that need multilagul support and it has a 131072 context lingth.
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## Bias, Risks, and Limitations
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it can some times produce a wrong answer.
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### Recommendations
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NOTE:you shold have lm studio or ollama to use this model
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IN LM-STUDIO:it is recommended to use this model with the defult lm-studio configration.
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IN OLLAMA: we will be pushing the model soon to ollama.
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## Training Details
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model trained with unsloth.
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### Training Data
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the training dataset that i used: https://huggingface.co/datasets/arbml/alpaca_arabic
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## IMPORTANT LINKS
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OLLAMA: https://ollama.com
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LM-STUDIO: https://lmstudio.ai
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llama3.1: instruct: https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
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dataset: https://huggingface.co/datasets/arbml/alpaca_arabic
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### Results
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![Screenshot 2024-08-14 141239.png](https://cdn-uploads.huggingface.co/production/uploads/650b3f38b5b6029d37298ae8/N-jYQm1uDwxeaAFZXZsPA.png)
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