Text Classification
Transformers
Safetensors
Chinese
bert
Generated from Trainer
text-embeddings-inference
Instructions to use roberthsu2003/for_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roberthsu2003/for_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="roberthsu2003/for_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("roberthsu2003/for_classification") model = AutoModelForSequenceClassification.from_pretrained("roberthsu2003/for_classification") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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model-index:
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- name: for_classification
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.50.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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model-index:
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- name: for_classification
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results: []
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license: apache-2.0
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datasets:
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- roberthsu2003/data_for_classification
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language:
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- zh
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.50.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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