Instructions to use wiorz/bert_pair_sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wiorz/bert_pair_sm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wiorz/bert_pair_sm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wiorz/bert_pair_sm") model = AutoModelForSequenceClassification.from_pretrained("wiorz/bert_pair_sm") - 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 sha256:1d443589c9e39ce03038e0d8bda07b1c9f67e58a280bca2a79672fc28b29d451
|
| 3 |
+
size 437962832
|