# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Marxav/frpron")
model = AutoModelForCausalLM.from_pretrained("Marxav/frpron", device_map="auto")Quick Links
Fr-word to phonemic pronunciation
This model aims at predicting the syllabized phonemic pronunciation of the French words.
The generated pronunciation is:
- A text string made of International Phonetic Alphabet (IPA) characters;
- Phonemic (i.e. remains at the phoneme-level, not deeper);
- Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).
Such pronunciation is used in the French Wiktionary in the {{pron|...|fr}} tag.
To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".
This model remains experimental. Additional finetuning is needed for:
The input length is currently limited to a maximum of 60 letters.
This work is derived from the OTEANN paper and code, which used minGTP.
More information on the model, dataset, hardware, environmental consideration:
The training data
The dataset used for training this models comes from data of the French Wiktionary.
The model
The model is build on gpt2
- Downloads last month
- 9
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Marxav/frpron")