Instructions to use FINDA-FIT/KLUE-ROBERTA_BASE_FALSE_FALSE_FALSE_FULL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FINDA-FIT/KLUE-ROBERTA_BASE_FALSE_FALSE_FALSE_FULL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FINDA-FIT/KLUE-ROBERTA_BASE_FALSE_FALSE_FALSE_FULL")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FINDA-FIT/KLUE-ROBERTA_BASE_FALSE_FALSE_FALSE_FULL") model = AutoModelForSequenceClassification.from_pretrained("FINDA-FIT/KLUE-ROBERTA_BASE_FALSE_FALSE_FALSE_FULL") - 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:e14050689b931f8064c18b32f4e0a135c6109376bf64dc0e06e6ed783cdf2d22
|
| 3 |
+
size 442513092
|