Update README.md

README.md

@@ -28,4 +28,30 @@ Using the [climatebert/distilroberta-base-climate-f](https://huggingface.co/clim
     institution={Available at SSRN 3998435},
     year={2023}
 }
+```
+
+## 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/climate_sentiment"
+model_name = "climatebert/distilroberta-base-climate-sentiment"
+
+# If you want to use your own data, simply load them as 🤗 Datasets dataset, see https://huggingface.co/docs/datasets/loading
+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)
 ```