Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use kmcjeong/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmcjeong/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kmcjeong/result")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kmcjeong/result") model = AutoModelForSequenceClassification.from_pretrained("kmcjeong/result") - Notebooks
- Google Colab
- Kaggle
kmcjeong/roberta-base-klue-ynat-classification
Browse files- model.safetensors +1 -1
- training_args.bin +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498628204
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:24d26a6047f4aa276cdbba9694afda435d1a32bef35214b1f727edd92cdfaec4
|
| 3 |
size 498628204
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5432
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3211449dc2182b625bfd34de74a7c0c7e592a889ba58786f876be41bda703b8a
|
| 3 |
size 5432
|