Instructions to use izaitova/gbert-large-topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use izaitova/gbert-large-topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="izaitova/gbert-large-topic_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("izaitova/gbert-large-topic_classification") model = AutoModelForSequenceClassification.from_pretrained("izaitova/gbert-large-topic_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bb7ea4ef350a3928f2bda1d1ee2806090e25cea0a6cd0ecf5d7c5c0396b79a3
- Size of remote file:
- 5.24 kB
- SHA256:
- 251ea9f82b6706a589d5692b346d0c90154dadcaccfdcbff0f57b5357e01327e
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