Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Vishnou/distilbert_base_SST2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vishnou/distilbert_base_SST2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Vishnou/distilbert_base_SST2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Vishnou/distilbert_base_SST2") model = AutoModelForSequenceClassification.from_pretrained("Vishnou/distilbert_base_SST2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a901b53c0d014c63ecf2c8c3695bbcc0a203ce309731b283b511cf0d110bf319
- Size of remote file:
- 4.6 kB
- SHA256:
- 1fab33e8477f921abf58c90ea9038adf39e0365b92b1591924bbff3bbf57fd39
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