Instructions to use ToBeWithYou/ABSA-Multi_Label_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ToBeWithYou/ABSA-Multi_Label_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ToBeWithYou/ABSA-Multi_Label_Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ToBeWithYou/ABSA-Multi_Label_Classification") model = AutoModelForSequenceClassification.from_pretrained("ToBeWithYou/ABSA-Multi_Label_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ToBeWithYou/ABSA-Multi_Label_Classification: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/training_args.bin
- Command line
-
hf download hf://ToBeWithYou/ABSA-Multi_Label_Classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 6af98a6c2248161e37b8e6815f78a97362fb63dad91d325850aaf61a902897c3
- Size of remote file:
- 5.05 kB
- SHA256:
- 9c4d8f7e299601fa00aa057a635af46f565eec928bc29fcc087b50505728e65a
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