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 tokenizer_config.json from ESGBERT/EnvRoBERTa-environmental: direct link, hf CLI and curl.
- Browser
- Download file 351 Bytes
-
https://huggingface.co/ESGBERT/EnvRoBERTa-environmental/resolve/c7272bfdea68d76d83cd8e3bee2f98d7c3a19c8b/tokenizer_config.json
- Command line
-
hf download hf://ESGBERT/EnvRoBERTa-environmental@c7272bfdea68d76d83cd8e3bee2f98d7c3a19c8b/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ESGBERT/EnvRoBERTa-environmental/resolve/c7272bfdea68d76d83cd8e3bee2f98d7c3a19c8b/tokenizer_config.json
351 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |