Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
Eval Results (legacy)
Instructions to use MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli") model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
VORTEXRAG: 7-Layer RAG — Causal Drift Filtering + Context Poison Guard [paper + code + demo]
#16 opened 2 months ago
by
vigneshwar234
License Conflict: MIT vs CC BY-NC 4.0
1
#15 opened about 1 year ago
by
qiuqiu666
Potential Inconsistencies Model and Datasets License
#13 opened about 1 year ago
by
yueyangchen
Add evaluation results on the default config of multi_nli
#4 opened almost 4 years ago
by
autoevaluator
Add evaluation results on the plain_text config of anli
#2 opened almost 4 years ago
by
autoevaluator