Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use aidiary/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aidiary/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aidiary/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aidiary/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("aidiary/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training completed!
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267867821
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fb54a574bee4dc65c81e6ff5c202d8e41d23b393beda812ca0994184b8134659
|
| 3 |
size 267867821
|