Instructions to use NLPScholars/Roberta-Earning-Call-Transcript-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPScholars/Roberta-Earning-Call-Transcript-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPScholars/Roberta-Earning-Call-Transcript-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification") model = AutoModelForSequenceClassification.from_pretrained("NLPScholars/Roberta-Earning-Call-Transcript-Classification") - Notebooks
- Google Colab
- Kaggle
Commit ·
a219408
1
Parent(s): 74d617a
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,6 +1,5 @@
|
|
| 1 |
---
|
| 2 |
widget:
|
| 3 |
- text: "Paytm’s Revenue Growth Trajectory To Remain Strong In Q1: Goldman Sachs"
|
| 4 |
-
- text: "Market cap of the firm fell to Rs 30,273 crore"
|
| 5 |
- text: "Nifty ends above 16,900, Sensex gains 1,041 pts led by IT, metal, realty"
|
| 6 |
---
|
|
|
|
| 1 |
---
|
| 2 |
widget:
|
| 3 |
- text: "Paytm’s Revenue Growth Trajectory To Remain Strong In Q1: Goldman Sachs"
|
|
|
|
| 4 |
- text: "Nifty ends above 16,900, Sensex gains 1,041 pts led by IT, metal, realty"
|
| 5 |
---
|