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 pytorch_model.bin from ESGBERT/EnvironmentalBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/ESGBERT/EnvironmentalBERT-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ESGBERT/EnvironmentalBERT-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ESGBERT/EnvironmentalBERT-base/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- 64cca866f77d04b75ddf9f7272a0474f712aa60239a45d5bc602a83474dc056c
- Size of remote file:
- 329 MB
- SHA256:
- 64640648b7ca20baadc6ce801d2bd78497bcb87ac643ceb4b2403176b04a5533
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