Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use kowsiknd/bert-base-uncased-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kowsiknd/bert-base-uncased-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kowsiknd/bert-base-uncased-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kowsiknd/bert-base-uncased-sst2") model = AutoModelForSequenceClassification.from_pretrained("kowsiknd/bert-base-uncased-sst2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:24df49fcdafd9a6565f8b8af5c44c75467c1c60dde678ed360d78f94f8f994d8
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size 437962832
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