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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ccdamian/test_classifier_bsc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 268 Bytes
9a04b2e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ---
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
--- |