Update model metadata to set pipeline tag to the new `text-ranking` and tags to `sentence-transformers`

Hello!

## Pull Request overview
* Update metadata to set pipeline tag to the new `text-ranking`
* Update metadata to set tags to `sentence-transformers`

## Changes
This is an automated pull request to update the metadata of the model card. We recently introduced the [`text-ranking`](https://huggingface.co/models?pipeline_tag=text-ranking) pipeline tag for models that are used for ranking tasks, and we have a suspicion that this model is one of them. I also updated added metadata to specify that this model can be loaded with the `sentence-transformers` library, as it should be possible to load any model compatible with `transformers` `AutoModelForSequenceClassification`.

Feel free to verify that it works with the following:

```bash
pip install sentence-transformers
```

```python
from sentence_transformers import CrossEncoder

model = CrossEncoder("TransferGraph/cross-encoder_quora-roberta-base-finetuned-lora-tweet_eval_emotion")
scores = model.predict([
("How many people live in Berlin?", "Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers."),
("How many people live in Berlin?", "Berlin is well known for its museums."),
])
print(scores)
```

Feel free to respond if you have questions or concerns.

- Tom Aarsen

README.md

@@ -4,11 +4,13 @@ library_name: peft
 tags:
 - parquet
 - text-classification
+- sentence-transformers
 datasets:
 - tweet_eval
 metrics:
 - accuracy
 base_model: cross-encoder/quora-roberta-base
+pipeline_tag: text-ranking
 model-index:
 - name: cross-encoder_quora-roberta-base-finetuned-lora-tweet_eval_emotion
   results: