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README.md
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metrics:
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- mse
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---
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For the model selection experiments llok at:
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https://wandb.ai/gec023/baseline-forecasting
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metrics:
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- mse
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---
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"""
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This script uses the Hugging Face model 'MRNH/Feedformer-ett-hourly' to perform some task on the ETT-small dataset.
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Model: 'MRNH/Feedformer-ett-hourly'
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- This model is a transformer-based model designed for some task. (Replace 'some task' with the actual task the model is designed for)
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Dataset: 'ETT-small'
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- This dataset contains... (Replace with a brief description of the dataset)
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The script performs the following steps:
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1. Load the 'MRNH/Feedformer-ett-hourly' model from the Hugging Face model hub.
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2. Load the 'ETT-small' dataset.
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3. Preprocess the dataset as required by the model.
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4. Feed the preprocessed data into the model and collect the outputs.
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5. Postprocess the outputs and save the results.
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Example:
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```python
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from transformers import AutoModel
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# Load the model
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model = AutoModel.from_pretrained('MRNH/Feedformer-ett-hourly')
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# Load your dataset here
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# dataset = ...
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# Preprocess your dataset here
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# preprocessed_data = ...
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# Feed the data into the model
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# outputs = model(preprocessed_data)
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# Postprocess and save the results
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# results = ...
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For the model selection experiments llok at:
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https://wandb.ai/gec023/baseline-forecasting
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