Token Classification
Transformers
PyTorch
bert
belarusian
bulgarian
macedonian
russian
serbian
ukrainian
pos
dependency-parsing
Instructions to use KoichiYasuoka/bert-base-slavic-cyrillic-upos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/bert-base-slavic-cyrillic-upos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/bert-base-slavic-cyrillic-upos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-slavic-cyrillic-upos") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-slavic-cyrillic-upos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
5a8ee02
1
Parent(s): b546aab
model improved
Browse files
supar.model → esupar.model
RENAMED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:de5e53536eb3bec292b0fa33842c1acc407be2b4b4eb8ada936eabd00da98007
|
| 3 |
+
size 811679896
|