Instructions to use climatebert/netzero-reduction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use climatebert/netzero-reduction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="climatebert/netzero-reduction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("climatebert/netzero-reduction") model = AutoModelForSequenceClassification.from_pretrained("climatebert/netzero-reduction", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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from tqdm.auto import tqdm
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dataset_name = "climatebert/climate_detection"
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tokenizer_name =
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model_name = "climatebert/netzero-reduction"
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# If you want to use your own data, simply load them as 🤗 Datasets dataset, see https://huggingface.co/docs/datasets/loading
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from tqdm.auto import tqdm
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dataset_name = "climatebert/climate_detection"
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tokenizer_name = "climatebert/distilroberta-base-climate-f"
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model_name = "climatebert/netzero-reduction"
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# If you want to use your own data, simply load them as 🤗 Datasets dataset, see https://huggingface.co/docs/datasets/loading
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