Instructions to use LogicSpine/address-base-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LogicSpine/address-base-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="LogicSpine/address-base-text-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LogicSpine/address-base-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("LogicSpine/address-base-text-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,8 +14,6 @@ pipeline_tag: zero-shot-classification
|
|
| 14 |
library_name: transformers
|
| 15 |
---
|
| 16 |
|
| 17 |
-
- Problem type: Text Classification
|
| 18 |
-
|
| 19 |
# LogicSpine/roberta-base-Address-classifier
|
| 20 |
|
| 21 |
## Model Description
|
|
|
|
| 14 |
library_name: transformers
|
| 15 |
---
|
| 16 |
|
|
|
|
|
|
|
| 17 |
# LogicSpine/roberta-base-Address-classifier
|
| 18 |
|
| 19 |
## Model Description
|