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 model.safetensors from ToBeWithYou/ABSA-Multi_Label_Classification: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/model.safetensors
- Command line
-
hf download hf://ToBeWithYou/ABSA-Multi_Label_Classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/model.safetensors
711 MB
- Xet hash:
- 848cac1c5b035be4c8f18f86a6d2d826a9d675c861bbfa846766e4c839a074f6
- Size of remote file:
- 711 MB
- SHA256:
- d3774613dfe3d903fca5390858bf4818a87adaa477d6a5e7ce51cbfc51270acb
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