Text Classification
Transformers
PyTorch
English
roberta
climate
climate change
text-embeddings-inference
Instructions to use gorgilazarev3/climatecognize-climate-topic-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gorgilazarev3/climatecognize-climate-topic-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gorgilazarev3/climatecognize-climate-topic-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gorgilazarev3/climatecognize-climate-topic-detection") model = AutoModelForSequenceClassification.from_pretrained("gorgilazarev3/climatecognize-climate-topic-detection") - Notebooks
- Google Colab
- Kaggle
ClimateCognize - Climate Topic Detection
This model is fine-tuned on sentences and paragraphs for the task of climate topic detection - whether a given text (ex. paragraph or sentence) is about climate or not.
The base model that this model is further trained on is the ClimateBERT Base Climate Detector and is further trained on our own datasets that include sentences and paragraphs from different news articles about climate, as well as negative examples such as excerpts from news articles that are completely different.
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