Instructions to use mk9165/mk-bert-sentiment-classification-4labels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mk9165/mk-bert-sentiment-classification-4labels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mk9165/mk-bert-sentiment-classification-4labels")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mk9165/mk-bert-sentiment-classification-4labels") model = AutoModelForSequenceClassification.from_pretrained("mk9165/mk-bert-sentiment-classification-4labels") - 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:a937690fd2ebb91c1f8d30759b1c3a772282887c8213f30df98e6138036e387e
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size 473229416
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