Text Classification
Transformers
PyTorch
Safetensors
Chinese
bert
classification
text-embeddings-inference
Instructions to use Herais/pred_timeperiod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Herais/pred_timeperiod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Herais/pred_timeperiod")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Herais/pred_timeperiod") model = AutoModelForSequenceClassification.from_pretrained("Herais/pred_timeperiod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a18e3130bb7c3c3eeca2642fb42a8e1c69cc281719bba68c52830fd686097f58
- Size of remote file:
- 409 MB
- SHA256:
- aacb9ede1e0ed2af50bbbd90e1a8571d01142918f4cb3d270450546cdd5c488e
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