Instructions to use garNER/bert-base-multilingual-cased-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garNER/bert-base-multilingual-cased-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="garNER/bert-base-multilingual-cased-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("garNER/bert-base-multilingual-cased-multi") model = AutoModelForTokenClassification.from_pretrained("garNER/bert-base-multilingual-cased-multi") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2e65f31e81a60674ca7c320b9b26903245f0ee4182c463dbd7ec1a42b74f167a
|
| 3 |
+
size 709288104
|