Instructions to use zcahjl3/STORY_ERROR_CLASSIFICATION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcahjl3/STORY_ERROR_CLASSIFICATION with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zcahjl3/STORY_ERROR_CLASSIFICATION")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION") model = AutoModelForSequenceClassification.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f42e1344c0d2c09be61a24eec38276b6501af5d5feca7e06e46ad63f023b9b90
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size 267838720
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