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

Hello!

## Pull Request overview
* Update metadata to set pipeline tag to the new `text-ranking`
* Update metadata to set library name 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("BAAI/bge-reranker-large")
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

@@ -5,14 +5,16 @@ language:
 - zh
 tags:
 - mteb
+pipeline_tag: text-ranking
+library_name: sentence-transformers
 model-index:
 - name: bge-reranker-base
   results:
   - task:
       type: Reranking
     dataset:
-      type: C-MTEB/CMedQAv1-reranking
       name: MTEB CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
       config: default
       split: test
       revision: None
@@ -24,8 +26,8 @@ model-index:
   - task:
       type: Reranking
     dataset:
-      type: C-MTEB/CMedQAv2-reranking
       name: MTEB CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
       config: default
       split: test
       revision: None
@@ -37,8 +39,8 @@ model-index:
   - task:
       type: Reranking
     dataset:
-      type: C-MTEB/Mmarco-reranking
       name: MTEB MMarcoReranking
+      type: C-MTEB/Mmarco-reranking
       config: default
       split: dev
       revision: None
@@ -50,8 +52,8 @@ model-index:
   - task:
       type: Reranking
     dataset:
-      type: C-MTEB/T2Reranking
       name: MTEB T2Reranking
+      type: C-MTEB/T2Reranking
       config: default
       split: dev
       revision: None
@@ -60,7 +62,6 @@ model-index:
       value: 67.27728847727172
     - type: mrr
       value: 77.1315192743764
-pipeline_tag: feature-extraction
 ---
 
 **We have updated the [new reranker](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/llm_reranker), supporting larger lengths, more languages, and achieving better performance.**