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") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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This model predicts the time period given a synopsis of about 200 Chinese characters.
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The model is trained on TV and Movie datasets and takes simplified Chinese as input.
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---
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language:
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- zh
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tags:
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- classification
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license: apache-2.0
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datasets:
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- Custom
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metrics:
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- rouge
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This model predicts the time period given a synopsis of about 200 Chinese characters.
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The model is trained on TV and Movie datasets and takes simplified Chinese as input.
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