Text Classification
Transformers
Safetensors
English
roberta
sentiment-analysis
finance
climate
esg
sustainability
green-finance
distilroberta
Eval Results (legacy)
text-embeddings-inference
Instructions to use peyterho/climatebert-macro-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peyterho/climatebert-macro-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peyterho/climatebert-macro-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peyterho/climatebert-macro-sentiment") model = AutoModelForSequenceClassification.from_pretrained("peyterho/climatebert-macro-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52425857258ed30367dc0285bb955e093761bb865c910d64a666ce8c6532f271
- Size of remote file:
- 5.33 kB
- SHA256:
- 8d6b48427ac9b032ef21015da4d23f8db6dd53dd913924a7d9314c590183fc69
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