Instructions to use Peraboom/SBertV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Peraboom/SBertV1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Peraboom/SBertV1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Peraboom/SBertV1") model = AutoModelForSequenceClassification.from_pretrained("Peraboom/SBertV1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 089a3a032d6867433ef4ea491ac87958636fb08be1a3b5d1e6dbf6f6b81d5896
- Size of remote file:
- 119 MB
- SHA256:
- 3f5af9d7d11dd3b978f242ba8b8c5306e4d5d01fb4b7f9d5537bf1a74a274175
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