Instructions to use ccdamian/test_classifier_bsc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccdamian/test_classifier_bsc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ccdamian/test_classifier_bsc")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ccdamian/test_classifier_bsc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ccdamian/test_classifier_bsc: direct link, hf CLI and curl.
- Browser
- Download file 268 Bytes
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https://huggingface.co/ccdamian/test_classifier_bsc/resolve/main/README.md
- Command line
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hf download hf://ccdamian/test_classifier_bsc/README.md
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curl -L -o README.md https://huggingface.co/ccdamian/test_classifier_bsc/resolve/main/README.md
268 Bytes
| license: unknown | |
| datasets: | |
| - gserafico/IMDB_Dataset | |
| language: | |
| - es | |
| - en | |
| metrics: | |
| - accuracy | |
| base_model: | |
| - distilbert/distilbert-base-uncased | |
| pipeline_tag: text-classification | |
| library_name: transformers | |
| tags: | |
| - text-classification | |
| - sentiment-analysis | |
| - reviews | |