Instructions to use dejanai/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanai/sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dejanai/sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dejanai/sentiment") model = AutoModelForSequenceClassification.from_pretrained("dejanai/sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,6 +1,7 @@
|
|
| 1 |
---
|
| 2 |
license: bigscience-openrail-m
|
| 3 |
pipeline_tag: text-classification
|
|
|
|
| 4 |
widget:
|
| 5 |
- example_title: Example 1
|
| 6 |
text: >-
|
|
|
|
| 1 |
---
|
| 2 |
license: bigscience-openrail-m
|
| 3 |
pipeline_tag: text-classification
|
| 4 |
+
base_model: albert-base-v2
|
| 5 |
widget:
|
| 6 |
- example_title: Example 1
|
| 7 |
text: >-
|