Instructions to use ganjubas2008/absa-rubert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ganjubas2008/absa-rubert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ganjubas2008/absa-rubert-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ganjubas2008/absa-rubert-tiny") model = AutoModelForSequenceClassification.from_pretrained("ganjubas2008/absa-rubert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ganjubas2008/absa-rubert-tiny: direct link, hf CLI and curl.
- Browser
- Download file 47.2 MB
-
https://huggingface.co/ganjubas2008/absa-rubert-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ganjubas2008/absa-rubert-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ganjubas2008/absa-rubert-tiny/resolve/main/pytorch_model.bin
47.2 MB
- Xet hash:
- f4497bffe987bdd787dfa841fae38f2f201afb58550fd22eed0d70a5213371a7
- Size of remote file:
- 47.2 MB
- SHA256:
- d5ddbc3ad3aefa0e2b34c7b8528f0cd2e2c53d9940989260bbe5976dd8226688
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