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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peyterho/climatebert-macro-sentiment") model = AutoModelForSequenceClassification.from_pretrained("peyterho/climatebert-macro-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from peyterho/climatebert-macro-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 3.6 MB
-
https://huggingface.co/peyterho/climatebert-macro-sentiment/resolve/main/tokenizer.json
- Command line
-
hf download hf://peyterho/climatebert-macro-sentiment/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/peyterho/climatebert-macro-sentiment/resolve/main/tokenizer.json
3.6 MB
File too large to display, you can check the raw version instead.