Instructions to use thu-coai/roberta-base-cdconv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thu-coai/roberta-base-cdconv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thu-coai/roberta-base-cdconv")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thu-coai/roberta-base-cdconv") model = AutoModelForSequenceClassification.from_pretrained("thu-coai/roberta-base-cdconv") - 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:e3823cecef855b8e37396d6d77b057c96bd854b2c226ae0d17ea93d61777a693
|
| 3 |
+
size 409104428
|