Zero-Shot Classification
Transformers
PyTorch
ONNX
Safetensors
deberta-v2
text-classification
nli
Eval Results (legacy)
Instructions to use MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7") model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7") - Inference
- Notebooks
- Google Colab
- Kaggle
License Conflict: MIT vs CC BY-NC 4.0
1
#11 opened 12 months ago
by
qiuqiu666
Interpretation Text/Sec , Speed Decreases with Text Length and Speed impact of Increase of number of labels (multi lable)
2
#10 opened about 1 year ago
by
thedamsch
How to load onnxx model
#6 opened over 2 years ago
by
erickdp
fine tune
4
#4 opened over 2 years ago
by
mansoorhamidzadeh
changing to num_labels 2
1
#2 opened over 3 years ago
by
3r1c