Text Classification
Transformers
PyTorch
Safetensors
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use hplisiecki/polemo_intensity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hplisiecki/polemo_intensity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hplisiecki/polemo_intensity")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hplisiecki/polemo_intensity") model = AutoModel.from_pretrained("hplisiecki/polemo_intensity") - Notebooks
- Google Colab
- Kaggle
Training time and resoruces
#1
by adendek - opened
Dear authors,
Could you please share the resources (time and hardware) that were needed to train or finetune this model?
We conducted the training on a V100 GPU in Google Colab with a batch size of 100. On average, it took about 2 seconds per epoch, and we performed 10 epochs in one sweep.
However, the model is small enough to fit into even an 8 GB GPU. Training would also work on such a GPU, but it would take significantly longer.