Text Classification
Transformers
PyTorch
Safetensors
English
roberta
ClimateBERT
climate
text-embeddings-inference
Instructions to use climatebert/environmental-claims with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use climatebert/environmental-claims with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="climatebert/environmental-claims")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("climatebert/environmental-claims") model = AutoModelForSequenceClassification.from_pretrained("climatebert/environmental-claims", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add metadata tag to model card metadata
To help make your model more discoverable to domain experts, I suggest adding a `climate` tag to the metadata for your model.6e9d801
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- Adding `safetensors` variant of this model (ab6178ead5b2f764b4187190a3d69af07a73c380) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a961f44
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