Instructions to use Data-Lab/ruRoberta-large_classification_v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data-Lab/ruRoberta-large_classification_v0.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Data-Lab/ruRoberta-large_classification_v0.2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Data-Lab/ruRoberta-large_classification_v0.2") model = AutoModelForSequenceClassification.from_pretrained("Data-Lab/ruRoberta-large_classification_v0.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Data-Lab/ruRoberta-large_classification_v0.2: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Data-Lab/ruRoberta-large_classification_v0.2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Data-Lab/ruRoberta-large_classification_v0.2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Data-Lab/ruRoberta-large_classification_v0.2/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 6e009b7e96d4825526046450d4aca34c520bdbed385cfa14a6693ff90619895b
- Size of remote file:
- 1.42 GB
- SHA256:
- d42a7870dea74a7c8cea925757ef5dc67adb31596a57b72b84a0c070b657e96c
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