Text Classification
Transformers
Safetensors
English
roberta
emotion
emotions
multi-class-classification
multi-label-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use minuva/MiniLMv2-goemotions-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minuva/MiniLMv2-goemotions-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minuva/MiniLMv2-goemotions-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minuva/MiniLMv2-goemotions-v2") model = AutoModelForSequenceClassification.from_pretrained("minuva/MiniLMv2-goemotions-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -20,6 +20,7 @@ model-index:
|
|
| 20 |
- name: F1
|
| 21 |
type: f1
|
| 22 |
value: 0.487
|
|
|
|
| 23 |
---
|
| 24 |
|
| 25 |
# Text Classification GoEmotions
|
|
@@ -56,5 +57,4 @@ The following hyperparameters were used during training:
|
|
| 56 |
|
| 57 |
# Deployment
|
| 58 |
|
| 59 |
-
Check out our [fast-nlp-text-emotion repository](https://github.com/minuva/fast-nlp-text-emotion) for a FastAPI based server to easily deploy this model on CPU devices.
|
| 60 |
-
|
|
|
|
| 20 |
- name: F1
|
| 21 |
type: f1
|
| 22 |
value: 0.487
|
| 23 |
+
license: apache-2.0
|
| 24 |
---
|
| 25 |
|
| 26 |
# Text Classification GoEmotions
|
|
|
|
| 57 |
|
| 58 |
# Deployment
|
| 59 |
|
| 60 |
+
Check out our [fast-nlp-text-emotion repository](https://github.com/minuva/fast-nlp-text-emotion) for a FastAPI based server to easily deploy this model on CPU devices.
|
|
|