Token Classification
Transformers
Safetensors
xmod
code-switching
language-identification
child-speech
multilingual
Instructions to use ZurichNLP/SwissBERT-CS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZurichNLP/SwissBERT-CS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ZurichNLP/SwissBERT-CS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ZurichNLP/SwissBERT-CS") model = AutoModelForTokenClassification.from_pretrained("ZurichNLP/SwissBERT-CS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
fc9bbe6
1
Parent(s): 9029278
Add model card metadata
Browse files
README.md
CHANGED
|
@@ -7,7 +7,7 @@ language:
|
|
| 7 |
license: mit
|
| 8 |
library_name: transformers
|
| 9 |
pipeline_tag: token-classification
|
| 10 |
-
base_model: ZurichNLP/
|
| 11 |
tags:
|
| 12 |
- code-switching
|
| 13 |
- language-identification
|
|
|
|
| 7 |
license: mit
|
| 8 |
library_name: transformers
|
| 9 |
pipeline_tag: token-classification
|
| 10 |
+
base_model: ZurichNLP/swissbert
|
| 11 |
tags:
|
| 12 |
- code-switching
|
| 13 |
- language-identification
|