Instructions to use ESGBERT/EnvironmentalBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ESGBERT/EnvironmentalBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ESGBERT/EnvironmentalBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ESGBERT/EnvironmentalBERT-base") model = AutoModelForMaskedLM.from_pretrained("ESGBERT/EnvironmentalBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ESGBERT/EnvironmentalBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/ESGBERT/EnvironmentalBERT-base/resolve/main/training_args.bin
- Command line
-
hf download hf://ESGBERT/EnvironmentalBERT-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ESGBERT/EnvironmentalBERT-base/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- bdfeb2e24a13aee4ae6b41d024edf0e26e2a33438d7336451b2cd8f119cca7d8
- Size of remote file:
- 4.09 kB
- SHA256:
- 77dc46c04bcdbcd84385c6e2f1bd452401074b29dce31632b054e77bae63f512
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