Update README.md with correct model name in "Direct use for inference" (#3)

- Update README.md with correct model name in "Direct use for inference" (d1d4d029b7edbf419533605654123c4cd7e676ea)
- Naming typos in code snippets (9d960ca3af3f5bc9a57d6e810dfd4cd2d2d860fd)


Co-authored-by: Krum Arnaudov <[email protected]>

README.md

@@ -155,7 +155,7 @@ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained
 from span_marker import SpanMarkerModel
 
 # Download from the 🤗 Hub
-model = SpanMarkerModel.from_pretrained("guishe/span-marker-generic-entity_recognition-v1-fewnerd-fine-super")
+model = SpanMarkerModel.from_pretrained("guishe/span-marker-generic-ner-v1-fewnerd-fine-super")
 # Run inference
 entities = model.predict("Most of the Steven Seagal movie \"Under Siege \"(co-starring Tommy Lee Jones) was filmed on the, which is docked on Mobile Bay at Battleship Memorial Park and open to the public.")
 ```
@@ -169,7 +169,7 @@ You can finetune this model on your own dataset.
 from span_marker import SpanMarkerModel, Trainer
 
 # Download from the 🤗 Hub
-model = SpanMarkerModel.from_pretrained("guishe/span-marker-generic-entity_recognition-v1-fewnerd-fine-super")
+model = SpanMarkerModel.from_pretrained("guishe/span-marker-generic-ner-v1-fewnerd-fine-super")
 
 # Specify a Dataset with "tokens" and "ner_tag" columns
 dataset = load_dataset("conll2003") # For example CoNLL2003
@@ -181,7 +181,7 @@ trainer = Trainer(
     eval_dataset=dataset["validation"],
 )
 trainer.train()
-trainer.save_model("guishe/span-marker-generic-entity_recognition-v1-fewnerd-fine-super-finetuned")
+trainer.save_model("guishe/span-marker-generic-ner-v1-fewnerd-fine-super-finetuned")
 ```
 </details>