Update README.md

Added How to use, as I can't get the tokenizer to load from the web interface.

README.md

@@ -33,6 +33,24 @@ Feed a corpus of tweets to the model to generate label if input is indicative of
 
 Limitation: All token sequences longer than 512 are automatically truncated.
 
+### How to use
+
+You can use this model directly with a pipeline for sentiment analysis:
+
+```python
+>>> from transformers import DistilBertTokenizerFast, AutoTokenizer
+>>> tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')
+>>> from transformers import DistilBertForSequenceClassification
+>>> model = DistilBertForSequenceClassification.from_pretrained(r"distilbert-depression-base")
+>>> from transformers import pipeline
+>>> classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+>>> tokenizer_kwargs = {'padding':True,'truncation':True,'max_length':512}
+>>> result=classifier('pain peko',**tokenizer_kwargs) #For truncation to apply in the pipeline
+
+
+[{'label': 'LABEL_1', 'score': 0.5048992037773132}]
+```
+
 ## Training hyperparameters
 
 The following hyperparameters were used during training: