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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge - GGUF
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- Model creator: https://huggingface.co/SongTonyLi/
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- Original model: https://huggingface.co/SongTonyLi/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge/
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q2_K.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q2_K.gguf) | Q2_K | 1.07GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_XS.gguf) | IQ3_XS | 1.2GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_S.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_S.gguf) | IQ3_S | 1.25GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_S.gguf) | Q3_K_S | 1.25GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_M.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ3_M.gguf) | IQ3_M | 1.34GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K.gguf) | Q3_K | 1.43GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_M.gguf) | Q3_K_M | 1.43GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q3_K_L.gguf) | Q3_K_L | 1.55GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ4_XS.gguf) | IQ4_XS | 1.54GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_0.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_0.gguf) | Q4_0 | 1.62GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.IQ4_NL.gguf) | IQ4_NL | 1.62GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K_S.gguf) | Q4_K_S | 1.62GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K.gguf) | Q4_K | 1.76GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_K_M.gguf) | Q4_K_M | 1.76GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_1.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q4_1.gguf) | Q4_1 | 1.79GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_0.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_0.gguf) | Q5_0 | 1.96GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K_S.gguf) | Q5_K_S | 1.96GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K.gguf) | Q5_K | 2.06GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_K_M.gguf) | Q5_K_M | 2.06GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_1.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q5_1.gguf) | Q5_1 | 2.13GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q6_K.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q6_K.gguf) | Q6_K | 2.32GB |
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| [OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q8_0.gguf](https://huggingface.co/RichardErkhov/SongTonyLi_-_OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge-gguf/blob/main/OpenELM-3B-SFT-D_chosen-HuggingFaceH4-ultrafeedback_binarized-Xlarge.Q8_0.gguf) | Q8_0 | 3.01GB |
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Original model description:
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---
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library_name: transformers
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tags:
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- trl
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- sft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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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:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [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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<!-- 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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[More Information Needed]
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### Out-of-Scope Use
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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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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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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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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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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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[More Information Needed]
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## Training Details
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### Training Data
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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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#### 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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[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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## 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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