Text Classification
Transformers
Safetensors
English
roberta
social-science
computational-social-science
situation-entity
genericity
discourse-modes
isaac
disco
Eval Results (legacy)
text-embeddings-inference
Instructions to use ISAAC-corpus/isaac-generalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ISAAC-corpus/isaac-generalization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ISAAC-corpus/isaac-generalization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ISAAC-corpus/isaac-generalization") model = AutoModelForSequenceClassification.from_pretrained("ISAAC-corpus/isaac-generalization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ISAAC-corpus/isaac-generalization: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/ISAAC-corpus/isaac-generalization/resolve/main/training_args.bin
- Command line
-
hf download hf://ISAAC-corpus/isaac-generalization/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ISAAC-corpus/isaac-generalization/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 4f67902b20b2a1dc05285cd1ba6f335b7757ed7a690c15eb6fe7073ad4e4c6da
- Size of remote file:
- 3.45 kB
- SHA256:
- 3d55a2fbf59a2f7b6d32bb381de952dcb0e272397357927baea76deec7684f72
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