Instructions to use seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka") model = AutoModelForSequenceClassification.from_pretrained("seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- 48f027e686f79f76bf8b371afda12ae4856a3658d2bf4cb270772fb7dada40ef
- Size of remote file:
- 711 MB
- SHA256:
- 076177b670ca1018924778e0402b23624f6d5609f771ee9dfb7d6bd76e0799b0
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