Update README.md

README.md

@@ -63,29 +63,15 @@ We evaluated CommonLingua in texts/sec (one paragraph = one text, ≤ 512 bytes
 | Sapphire Rapids CPU (8 threads) | bs=32      | 183 | **553** | 3.0× |
 | Sapphire Rapids CPU (1 thread)  | bs=32      | 44 | **114** | 2.6×|
 
-## Quick start
+## Inference
 
-```bash
-pip install "git+https://github.com/PleIAs/bytehybrid-lid#egg=commonlingua[hub]"
-```
+Easiest way to test the model is to test the provided predict.py script:
 
 ```python
-from commonlingua import LID
-
-lid = LID.from_pretrained("PleIAs/CommonLingua")          # auto-downloads
-# Use the bf16 build for 2× speedup on GPU at no measurable quality cost:
-# lid = LID.from_pretrained("PleIAs/CommonLingua", dtype="bf16")
-
-text = (
-    "Wikipédia est une encyclopédie universelle, multilingue, créée par Jimmy "
-    "Wales et Larry Sanger le 15 janvier 2001 et fonctionnant selon le principe "
-    "du wiki."
-)
-r = lid.predict(text)
-print(r.lang, r.confidence)   # fra 0.99
+python predict.py "Wikipédia est une encyclopédie universelle, multilingue."  # fra 0.99
 ```
 
-The intended workload is **paragraph-level corpus curation**. For batch annotation of large parquet shards, see `predict_parquet` in the package README.
+The intended workload is paragraph-level corpus curation. CommonLingua was not assessed on very short text segments and will likely perform less well than alternatives.
 
 
 ## Citation