---
datasets:
- yjseo/etth1_for_llm2
- yjseo/etth1_for_llm
metrics:
- mse
---

This script uses the Hugging Face model 'MRNH/Feedformer-ett-hourly' to perform some task on the ETT-small dataset.

Model: 'MRNH/Feedformer-ett-hourly'
- This model is a transformer-based model designed for some task. (Replace 'some task' with the actual task the model is designed for)

Dataset: 'ETT-small'
- This dataset contains... (Replace with a brief description of the dataset)

The script performs the following steps:
1. Load the 'MRNH/Feedformer-ett-hourly' model from the Hugging Face model hub.
2. Load the 'ETT-small' dataset.
3. Preprocess the dataset as required by the model.
4. Feed the preprocessed data into the model and collect the outputs.
5. Postprocess the outputs and save the results.


Example:
  from transformers import AutoModel
  model = AutoModel.from_pretrained('MRNH/Feedformer-ett-hourly')

  

For the model selection experiments llok at:
  https://wandb.ai/gec023/baseline-forecasting