Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use LKriesch/TwinTransitionMapper_AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use LKriesch/TwinTransitionMapper_AI with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("LKriesch/TwinTransitionMapper_AI") - sentence-transformers
How to use LKriesch/TwinTransitionMapper_AI with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LKriesch/TwinTransitionMapper_AI") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,7 +14,7 @@ inference: true
|
|
| 14 |
---
|
| 15 |
|
| 16 |
# TwinTransitionMapper_AI
|
| 17 |
-
This repository contains the model for our paper entitled Not all twins are identical: the digital layer of “twin” transition market applications
|
| 18 |
|
| 19 |
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
|
| 20 |
|
|
|
|
| 14 |
---
|
| 15 |
|
| 16 |
# TwinTransitionMapper_AI
|
| 17 |
+
This repository contains the model for our paper entitled [Not all twins are identical: the digital layer of “twin” transition market applications](https://drive.google.com/file/d/1MN0GSl1FExHYkDyN_VhEt8yFwMX1MM4x/view?usp=drive_link) which is under review in Regional Studies (https://www.tandfonline.com/journals/cres20).
|
| 18 |
|
| 19 |
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
|
| 20 |
|