Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use semindan/xnli_m_bert_only_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use semindan/xnli_m_bert_only_de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="semindan/xnli_m_bert_only_de")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("semindan/xnli_m_bert_only_de") model = AutoModelForSequenceClassification.from_pretrained("semindan/xnli_m_bert_only_de") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
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{
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"_name_or_path": "semindan/xnli_m_bert_only_de",
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"architectures": [
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"BertForSequenceClassification"
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],
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"_name_or_path": "/home/semindan/baka/src/xnli_m_bert_only_de/checkpoint-9204",
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"architectures": [
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"BertForSequenceClassification"
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pytorch_model.bin
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