Instructions to use FrinzTheCoder/bert-base-multilingual-cased-vmw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FrinzTheCoder/bert-base-multilingual-cased-vmw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FrinzTheCoder/bert-base-multilingual-cased-vmw")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-vmw") model = AutoModelForSequenceClassification.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-vmw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 4
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 711440380
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5d4914b9ce65a7ac4d63bc05b7f8ff85434b1d9162b1d83eea29ccf1a5cf0200
|
| 3 |
size 711440380
|