Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use schematise/ICAT-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use schematise/ICAT-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="schematise/ICAT-text-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("schematise/ICAT-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("schematise/ICAT-text-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-52/optimizer.pt from schematise/ICAT-text-classifier: direct link, hf CLI and curl.
- Browser
- Download file 876 MB
-
https://huggingface.co/schematise/ICAT-text-classifier/resolve/main/checkpoint-52/optimizer.pt
- Command line
-
hf download hf://schematise/ICAT-text-classifier/checkpoint-52/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/schematise/ICAT-text-classifier/resolve/main/checkpoint-52/optimizer.pt
876 MB
- Xet hash:
- 2cf9ef5c25b6a8c03ec705047a75204299398668a71ce2117e403f374c3c14c4
- Size of remote file:
- 876 MB
- SHA256:
- 1b6e69f4ab193c5d2bbf9509595aa36b77d8f0f33fcdf60f6ce40bfa030814e1
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