Text Classification
Transformers
PyTorch
Safetensors
English
roberta
climate
text-embeddings-inference
Instructions to use climatebert/distilroberta-base-climate-tcfd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use climatebert/distilroberta-base-climate-tcfd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="climatebert/distilroberta-base-climate-tcfd")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("climatebert/distilroberta-base-climate-tcfd") model = AutoModelForSequenceClassification.from_pretrained("climatebert/distilroberta-base-climate-tcfd") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3257ffd67001e2213e0f4af37321c8688b86edb1a20efe6ce1db113aff41a735
- Size of remote file:
- 329 MB
- SHA256:
- 1322f936a7c745c53eb7013f17263d50192ebcc9296e1f5b09c2e745e83093b8
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