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@@ -37,4 +37,166 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
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  tokenizer = AutoTokenizer.from_pretrained("x2bee/PLOAR-7B-DPO-v1.0")
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  model = AutoModelForCausalLM.from_pretrained("x2bee/PLOAR-7B-DPO-v1.0")
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  tokenizer = AutoTokenizer.from_pretrained("x2bee/PLOAR-7B-DPO-v1.0")
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  model = AutoModelForCausalLM.from_pretrained("x2bee/PLOAR-7B-DPO-v1.0")
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+ ```
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+
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+ ## Downstream Use [Optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+ <!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
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+
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+
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+ ## Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+ <!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
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+
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+ # Bias, Risks, and Limitations
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
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+
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+
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+ ## Recommendations
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+ # Training Details
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+ ## Training Data
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+ <!-- This should link to a Data 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 on training data 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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+ ### Preprocessing
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+ More information needed
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+ ### Speeds, Sizes, Times
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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 Data 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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+ More information needed
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+ ## Results
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+ More information needed
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+ # Model Examination
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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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+
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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
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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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+ If you would like more information about our company, please visit the link below.
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+ [tech.x2bee.com](https://tech.x2bee.com/)
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+ # Model Card Authors [optional]
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+ <!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
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+ Woomun Jung, MinYoung Joo, Eunsu Ha, Seungjun Son
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+ # Model Card Contact
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+ More information needed
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+ # How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ <details>
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+ <summary> Click to expand </summary>
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+ More information needed
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+ </details>