Instructions to use PlatschLena/support-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PlatschLena/support-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PlatschLena/support-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PlatschLena/support-classification") model = AutoModelForSequenceClassification.from_pretrained("PlatschLena/support-classification", device_map="auto") - 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:b8ec499802562c7a936600b1ebcc02860977125554ec2ff013e6f36c88afff19
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size 439743484
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