Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dinhlnd1610/distilbert-base-uncased-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
distilbert-base-uncased-finetuned-sst2 / runs /Dec06_08-42-17_486c67ed138d /events.out.tfevents.1701853704.486c67ed138d.2142.1
- Xet hash:
- 09c0cddec8ece2dbd3fb7a4d6f0556800cbffb1922139dcf64d6f858896a1f07
- Size of remote file:
- 4.94 kB
- SHA256:
- b399985a74b2a271ee42d05f055abfe8b8ce04fb886b5e2475d32a5647225241
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