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_08-35-51_486c67ed138d /events.out.tfevents.1701851766.486c67ed138d.257.0
- Xet hash:
- 3cb2db240e5c9097f026ae687d84f9deeb89cf5b7d845eb66877fa1ae5cf18ee
- Size of remote file:
- 5.74 kB
- SHA256:
- 63651a321f3f0e2ef0563d485abee1b4ee02b67e4b7351a02a8021ac0bd726b2
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