Instructions to use averageandyyy/review_to_condition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use averageandyyy/review_to_condition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="averageandyyy/review_to_condition")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("averageandyyy/review_to_condition") model = AutoModelForSequenceClassification.from_pretrained("averageandyyy/review_to_condition") - 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 sha256:8d91c2de5fd6b8cc71c96130917719c030f8ba2889b43f40802d949aea5b7f3d
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size 435649632
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