Instructions to use yangwang825/bert-base-uncased-mean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangwang825/bert-base-uncased-mean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangwang825/bert-base-uncased-mean", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangwang825/bert-base-uncased-mean", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("yangwang825/bert-base-uncased-mean", trust_remote_code=True, device_map="auto") - 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:a7b45d0176a78ff8dccb7e35a94b714d41a518d74287f88c6948a7d78698eb95
|
| 3 |
+
size 437958648
|