Text Classification
Transformers
TensorFlow
English
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use gopiashokan/Financial-Document-Classification-using-Deep-Learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gopiashokan/Financial-Document-Classification-using-Deep-Learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gopiashokan/Financial-Document-Classification-using-Deep-Learning")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gopiashokan/Financial-Document-Classification-using-Deep-Learning") model = AutoModelForSequenceClassification.from_pretrained("gopiashokan/Financial-Document-Classification-using-Deep-Learning") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -10,7 +10,12 @@ language:
|
|
| 10 |
- en
|
| 11 |
metrics:
|
| 12 |
- confusion_matrix
|
|
|
|
|
|
|
|
|
|
| 13 |
pipeline_tag: text-classification
|
|
|
|
|
|
|
| 14 |
---
|
| 15 |
|
| 16 |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
|
|
|
|
| 10 |
- en
|
| 11 |
metrics:
|
| 12 |
- confusion_matrix
|
| 13 |
+
- precision
|
| 14 |
+
- recall
|
| 15 |
+
- f1
|
| 16 |
pipeline_tag: text-classification
|
| 17 |
+
base_model:
|
| 18 |
+
- yiyanghkust/finbert-pretrain
|
| 19 |
---
|
| 20 |
|
| 21 |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
|