Instructions to use almanach/camembert-base-legacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/camembert-base-legacy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="almanach/camembert-base-legacy")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/camembert-base-legacy") model = AutoModelForMaskedLM.from_pretrained("almanach/camembert-base-legacy") - Inference
- Notebooks
- Google Colab
- Kaggle
Model has no tokenizer included in the dowload file
#2
by Bourhano - opened
Where can we find he tokenizer for this version of CamemBERT, and do all CamemBERT models proposed by this account 'camembert' use the same tokenizer? Since I already have a version of the tokenizer.json but do not recall where I got it from.
Edit:
It seems that the tockenizer differs between 'camembert-base' and 'camembert-large' according to the paper that introduces CamemBERT.
It mentions:
'The second and the third models, camembert-base and camembert-large, respectively, are based on the RoBERTa architecture (Liu et al., 2019), a BERT-based model with some changes (tokenizer, training task, optimization, etc.)'