Instructions to use VityaVitalich/bert-tiny-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VityaVitalich/bert-tiny-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VityaVitalich/bert-tiny-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VityaVitalich/bert-tiny-sst2") model = AutoModelForSequenceClassification.from_pretrained("VityaVitalich/bert-tiny-sst2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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:de963b280e4b6d54590f462c2103755cb72b10051eab3c7aebf83526682053cc
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size 8776876
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