Text Classification
Transformers
ONNX
Safetensors
PyTorch
English
multi-label-classification
multi-class-classification
emotion
bert
go_emotions
emotion-classification
sentiment-analysis
tensorflow
Eval Results (legacy)
Instructions to use logasanjeev/bert-emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use logasanjeev/bert-emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="logasanjeev/bert-emotion-classifier")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("logasanjeev/bert-emotion-classifier", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload model.safetensors for updated GoEmotions BERT model
Browse files- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:15d5181ffac4011c167e05d79d0bb0a7eff28875a52dc5673eb65fab65a186b8
|
| 3 |
+
size 438038624
|