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---
language: en
license: apache-2.0
tags:
- Env Claims
---
# Model Card for environmental-claims
## Model Description
Trained for specific Environmentional claims, for emerging markets models | - |
## Citation Information
@misc{stammbach2022environmentalclaims,
title = {A Dataset for Detecting Real-World Environmental Claims},
author = {Stammbach, Dominik and Webersinke, Nicolas and Bingler, Julia Anna and Kraus, Mathias and Leippold, Markus},
year = {2022},
}
@misc{
title = {Custom Emerging markets},
author = {Tushar Aggarwal},
year = {December 2022},
}
## How to Get Started With the Model
You can use the model with a pipeline for text classification:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
from transformers.pipelines.pt_utils import KeyDataset
import datasets
from tqdm.auto import tqdm
dataset_name = "climatebert/environmental_claims"
dataset = datasets.load_dataset(dataset_name, split="test")
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name, max_len=512)
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer, device=0)
# See https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline
for out in tqdm(pipe(KeyDataset(dataset, "text"), padding=True, truncation=True)):
print(out)
``` |