Instructions to use Neroism8422/Text_Classification_1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neroism8422/Text_Classification_1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neroism8422/Text_Classification_1000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neroism8422/Text_Classification_1000") model = AutoModelForSequenceClassification.from_pretrained("Neroism8422/Text_Classification_1000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c508154c1801f13515946604204558959e927f93e0aa3da8de35f62ac58f3cb
- Size of remote file:
- 268 MB
- SHA256:
- 6ac8acc02641692aa54fbf10e2799a25d108a354544ef3bd0a4577663867ba46
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