Text Classification
Transformers
PyTorch
Safetensors
English
bert
sst2
glue
torchdistill
text-embeddings-inference
Instructions to use yoshitomo-matsubara/bert-base-uncased-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yoshitomo-matsubara/bert-base-uncased-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yoshitomo-matsubara/bert-base-uncased-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yoshitomo-matsubara/bert-base-uncased-sst2") model = AutoModelForSequenceClassification.from_pretrained("yoshitomo-matsubara/bert-base-uncased-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot