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  library_name: transformers
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  tags:
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  - chess
 
 
 
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  license: apache-2.0
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  datasets:
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  - Q-bert/Elite-Chess-Games
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  ### Model Description
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  - **Developed by:** [Talha Rüzgar Akkuş](https://www.linkedin.com/in/talha-r%C3%BCzgar-akku%C5%9F-1b5457264/)
 
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  - **Model type:** [Llama Architecture](https://huggingface.co/docs/transformers/main/model_doc/llama)
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- - **License:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
 
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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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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  ### Downstream Use [optional]
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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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- #### Preprocessing [optional]
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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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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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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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- #### Hardware
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- #### Software
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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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- **APA:**
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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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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  library_name: transformers
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  tags:
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  - chess
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+ - llama
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+ - ChessLlama
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+ - chess-engines
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  license: apache-2.0
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  datasets:
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  - Q-bert/Elite-Chess-Games
 
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  ### Model Description
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  - **Developed by:** [Talha Rüzgar Akkuş](https://www.linkedin.com/in/talha-r%C3%BCzgar-akku%C5%9F-1b5457264/)
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+ - **Data Format:** [Universal Chess Interface (UCI)](https://en.wikipedia.org/wiki/Universal_Chess_Interface)
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  - **Model type:** [Llama Architecture](https://huggingface.co/docs/transformers/main/model_doc/llama)
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+ - **License:** [apache-2.0]()
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+ ## Usage
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+ This notebook is created to test the model's capabilities. You can use it to evaluate performance of the model.
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+ [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1guqb9xjvOalFQV7AKucaFN0D3Kd1SSzC?usp=sharing)
 
 
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  ### Downstream Use [optional]
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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. -->