Update README.md

README.md

@@ -18,7 +18,7 @@ pipeline_tag: token-classification
 ---
 
 ## INTRODUCTION:
-This model, developed as part of the [propp-fr project](https://github.com/lattice-8094/fr-litbank), is a **NER model** built on top of [camembert-large](https://huggingface.co/almanach/camembert-large) embeddings, trained to predict nested entities in french, specifically for literary texts.
+This model, developed as part of the [propp-fr project](https://lattice-8094.github.io/propp/), is a **NER model** built on top of [camembert-large](https://huggingface.co/almanach/camembert-large) embeddings, trained to predict nested entities in french, specifically for literary texts.
 
 The predicted entities are:
 - mentions of characters (PER): pronouns (je, tu, il, ...), possessive pronouns (mon, ton, son, ...), common nouns (le capitaine, la princesse, ...) and proper nouns (Indiana Delmare, Honoré de Pardaillan, ...)
@@ -67,7 +67,7 @@ Model Input: Maximum context camembert-large embeddings (1024 dimensions)
 Model Output: BIOES labels sequence
 
 ## HOW TO USE:
-*** IN CONSTRUCTION ***
+[Propp Documentation](https://lattice-8094.github.io/propp/quick_start/)
 
 ## TRAINING CORPUS:
 |    | Document                                                                        | Tokens Count   | Is included in model eval         |