Text Classification
Transformers
PyTorch
TensorBoard
ONNX
Chinese
bert
Generated from Trainer
text-embeddings-inference
Instructions to use xqchq/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xqchq/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xqchq/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xqchq/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("xqchq/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json
Browse files- config.json +1 -0
config.json
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{
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"_name_or_path": "hfl/minirbt-h256",
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"architectures": [
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"BertForSequenceClassification"
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],
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{
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"_name_or_path": "hfl/minirbt-h256",
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"_num_labels": 10,
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"architectures": [
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"BertForSequenceClassification"
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],
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