Text Classification
Transformers
PyTorch
English
roberta
ESG
environmental
text-embeddings-inference
Instructions to use ESGBERT/EnvironmentalBERT-environmental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ESGBERT/EnvironmentalBERT-environmental with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ESGBERT/EnvironmentalBERT-environmental")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ESGBERT/EnvironmentalBERT-environmental") model = AutoModelForSequenceClassification.from_pretrained("ESGBERT/EnvironmentalBERT-environmental", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbe9b2d0f319ce9d1f71721123afbcfe639604a2d56b4e34f71b47e96a3511a7
- Size of remote file:
- 329 MB
- SHA256:
- 9faf8330739bd08703cabef0c25fcdd744db95d1bc7979db9022aee9a4475f7b
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