Instructions to use DataCleaning/RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataCleaning/RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DataCleaning/RoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DataCleaning/RoBERTa") model = AutoModelForSequenceClassification.from_pretrained("DataCleaning/RoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload entire_model.pt
Browse files- entire_model.pt +3 -0
entire_model.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a8e1692ee434956b87ec0aded5e3fea8b741a05949290616a06471d1b94999c8
|
| 3 |
+
size 498791463
|