Instructions to use izaitova/ruBert-large-topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use izaitova/ruBert-large-topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="izaitova/ruBert-large-topic_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("izaitova/ruBert-large-topic_classification") model = AutoModelForSequenceClassification.from_pretrained("izaitova/ruBert-large-topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf33ed45e32c126453b739d0b5ecc282dea60d16a6070d2e270cc28ec742eca9
- Size of remote file:
- 1.71 GB
- SHA256:
- dc6d70100d71e2cb8402e7c05c0b0b3378c0545766c268c91db76e205bb16dfb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.