Zero-Shot Classification
Transformers
PyTorch
JAX
Safetensors
Norwegian
bert
text-classification
nb-bert
tensorflow
norwegian
Instructions to use NbAiLab/nb-bert-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-bert-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NbAiLab/nb-bert-base-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NbAiLab/nb-bert-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("NbAiLab/nb-bert-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -15,9 +15,9 @@ datasets:
|
|
| 15 |
- xnli
|
| 16 |
pipeline_tag: zero-shot-classification
|
| 17 |
widget:
|
| 18 |
-
- text: "
|
| 19 |
candidate_labels: "politikk, helse, sport, religion"
|
| 20 |
-
hypothesis_template: "
|
| 21 |
multi_class: true
|
| 22 |
---
|
| 23 |
|
|
|
|
| 15 |
- xnli
|
| 16 |
pipeline_tag: zero-shot-classification
|
| 17 |
widget:
|
| 18 |
+
- text: "Folkehelseinstituttets mest optimistiske anslag er at alle voksne er ferdigvaksinert innen midten av september."
|
| 19 |
candidate_labels: "politikk, helse, sport, religion"
|
| 20 |
+
hypothesis_template: "Dette eksempelet er {}."
|
| 21 |
multi_class: true
|
| 22 |
---
|
| 23 |
|