Text Classification
Transformers
Safetensors
English
roberta
policy
coherence
government
text-embeddings-inference
Instructions to use akaburia/policy-evaluations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akaburia/policy-evaluations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akaburia/policy-evaluations")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akaburia/policy-evaluations") model = AutoModelForSequenceClassification.from_pretrained("akaburia/policy-evaluations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
datasets:
|
| 4 |
+
- akaburia/policy-evaluations
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
metrics:
|
| 8 |
+
- recall
|
| 9 |
+
- precision
|
| 10 |
+
- f1
|
| 11 |
+
base_model:
|
| 12 |
+
- FacebookAI/roberta-large
|
| 13 |
+
library_name: transformers
|
| 14 |
+
tags:
|
| 15 |
+
- policy
|
| 16 |
+
- coherence
|
| 17 |
+
- government
|
| 18 |
+
---
|