Text Classification
Transformers
PyTorch
English
roberta
ESG
environmental
text-embeddings-inference
Instructions to use ESGBERT/EnvRoBERTa-environmental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ESGBERT/EnvRoBERTa-environmental with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ESGBERT/EnvRoBERTa-environmental")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ESGBERT/EnvRoBERTa-environmental") model = AutoModelForSequenceClassification.from_pretrained("ESGBERT/EnvRoBERTa-environmental", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from ESGBERT/EnvRoBERTa-environmental: direct link, hf CLI and curl.
- Browser
- Download file 798 kB
-
https://huggingface.co/ESGBERT/EnvRoBERTa-environmental/resolve/6cd314d0b2de9bddb3ae2845e4e402926022a7a5/vocab.json
- Command line
-
hf download hf://ESGBERT/EnvRoBERTa-environmental@6cd314d0b2de9bddb3ae2845e4e402926022a7a5/vocab.json
-
curl -L -o vocab.json https://huggingface.co/ESGBERT/EnvRoBERTa-environmental/resolve/6cd314d0b2de9bddb3ae2845e4e402926022a7a5/vocab.json
798 kB
File too large to display, you can check the raw version instead.