Text Classification
Transformers
Safetensors
English
roberta
climate
esg
environment
adaptation
binary-classification
text-embeddings-inference
distilroberta
Instructions to use ClimateLouie/AdaptationBERT-distil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClimateLouie/AdaptationBERT-distil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ClimateLouie/AdaptationBERT-distil")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ClimateLouie/AdaptationBERT-distil") model = AutoModelForSequenceClassification.from_pretrained("ClimateLouie/AdaptationBERT-distil", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# AdaptationBERT-distil
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A faster, distilled variant of [AdaptationBERT](https://huggingface.co/ClimateLouie/AdaptationBERT) for binary classification of climate adaptation and resilience texts in the ESG/environmental domain.
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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- roberta
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- climate
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- esg
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- environment
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- adaptation
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- binary-classification
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- text-embeddings-inference
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- distilroberta
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datasets:
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- ClimateLouie/AdaptationBERT-Climate
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base_model: ESGBERT/EnvironmentalBERT-base
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---
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# AdaptationBERT-distil
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A faster, distilled variant of [AdaptationBERT](https://huggingface.co/ClimateLouie/AdaptationBERT) for binary classification of climate adaptation and resilience texts in the ESG/environmental domain.
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