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 rng_state.pth from ToBeWithYou/ABSA-Multi_Label_Classification: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/rng_state.pth
- Command line
-
hf download hf://ToBeWithYou/ABSA-Multi_Label_Classification/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/ToBeWithYou/ABSA-Multi_Label_Classification/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 95e0223955bc9de33d1358b0d64bb0a81d4b8266412ade9f1cd9c9e3970d7eae
- Size of remote file:
- 14.2 kB
- SHA256:
- 5e4fce0acc26183ac2f083176e4a2c0d24a485c82047c0b767ae921debd353ee
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