Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use thanhcong2001/Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thanhcong2001/Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thanhcong2001/Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thanhcong2001/Sentiment") model = AutoModelForSequenceClassification.from_pretrained("thanhcong2001/Sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 934d47538d73c6fe31c6cbd068595bd05ab448fade28d0630d14ce54139a7f9e
- Size of remote file:
- 268 MB
- SHA256:
- 3852e43d6b0368501cc1abf4a9aa48542462f23fac6063d0f4476e11199c71d5
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