Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use kiatkock/sentiment_pc_combinedBase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kiatkock/sentiment_pc_combinedBase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kiatkock/sentiment_pc_combinedBase")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kiatkock/sentiment_pc_combinedBase") model = AutoModelForSequenceClassification.from_pretrained("kiatkock/sentiment_pc_combinedBase") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ac406360a9f9e4a5cb5a777ec3adc73a7f304ebb8d34c36012bdcbdccc03bad
- Size of remote file:
- 5.11 kB
- SHA256:
- f5693f4c6b86312728b3f84d8886ca2bfae71d7b00a32de5a42b010a6a295d31
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