Update README.md

README.md

@@ -17,21 +17,15 @@ The model is designed to be used to normalise 17th c. French texts. The best per
 
 ### How to use
 
-The model is to be used with the custom pipeline available in in the original repository [here](https://github.com/rbawden/ModFr-Norm/blob/main/hf-conversion/pipeline.py) and in this repository [here](https://huggingface.co/rbawden/modern_french_normalisation/blob/main/pipeline.py). You first need to download the pipeline file so that you can use it locally (since it is not integrated into HuggingFace).
+The model is to be used with the custom pipeline available in this repository (transformers>=4.21.0):
 
 ```
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from pipeline import NormalisationPipeline # N.B. local file
-
-cache_lexicon_path="~/.normalisation_lex.pickle" # optionally set a path to store the processed lexicon (speeds up loading)
-tokeniser = AutoTokenizer.from_pretrained("rbawden/modern_french_normalisation")
-model = AutoModelForSeq2SeqLM.from_pretrained("rbawden/modern_french_normalisation")
-norm_pipeline = NormalisationPipeline(model=model, tokenizer=tokeniser, batch_size=32, beam_size=5, cache_file=cache_lexicon_path)
+from transformers import pipeline
+normaliser = pipeline(model="rbawden/modern_french_normalisation", batch_size=32, beam_size=5, cache_file="./cache.pickle", trust_remote_code=True)
                                               
 list_inputs = ["Elle haïſſoit particulierement le Cardinal de Lorraine;", "Adieu, i'iray chez vous tantoſt vous rendre grace."]
-list_outputs = norm_pipeline(list_inputs)
+list_outputs = normaliser(list_inputs)
 print(list_outputs)
-
 >> [{'text': 'Elle haïssait particulièrement le Cardinal de Lorraine; ', 'alignment': [([0, 3], [0, 3]), ([5, 12], [5, 12]), ([14, 29], [14, 29]), ([31, 32], [31, 32]), ([34, 41], [34, 41]), ([43, 44], [43, 44]), ([46, 53], [46, 53]), ([54, 54], [54, 54])]}, {'text': "Adieu, j'irai chez vous tantôt vous rendre grâce. ", 'alignment': [([0, 4], [0, 4]), ([5, 5], [5, 5]), ([7, 8], [7, 8]), ([9, 12], [9, 12]), ([14, 17], [14, 17]), ([19, 22], [19, 22]), ([24, 30], [24, 29]), ([32, 35], [31, 34]), ([37, 42], [36, 41]), ([44, 48], [43, 47]), ([49, 49], [48, 48])]}]
 ```