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
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3208cc4ab5492c9fd88b687398d5c7495d199e95c8b5d62f2d53eb407bd72dd5
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size 711450724
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