zedfum
/

arman-longformer-8k

@@ -6,193 +6,6 @@ pipeline_tag: summarization
 # Model Card for Model arman-longformer-8k
 <!-- Provide a quick summary of what the model is/does. -->
-This model is only the extended model of alireza7/ARMAN-MSR-persian-base and should be fine-tuned for summarization tasks.
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
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-### Model Sources [optional]
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-## Uses
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-### Direct Use
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-[More Information Needed]
-### Downstream Use [optional]
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-Long Text Summarization
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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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
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-#### Speeds, Sizes, Times [optional]
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-## Evaluation
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-### Testing Data, Factors & Metrics
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-#### Factors
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-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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-## Technical Specifications [optional]
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 # Model Card for Model arman-longformer-8k
 <!-- Provide a quick summary of what the model is/does. -->
+This project use Longformer's attention mechanism to [alireza7/ARMAN-MSR-persian-base](https://huggingface.co/alireza7/ARMAN-MSR-persian-base) in order to perform abstractive summarization on long documents. so new model can accept 8K tokens (rather than 512 tokens).it should be fine-tuned for summarization tasks.