Modèles (PyTorch)

!pip install transformers[sentencepiece]

from transformers import CamembertConfig, CamembertModel

# Construire la configuration
config = CamembertConfig()

# Construire le modèle à partir de la configuration
model = CamembertModel(config)

print(config)

from transformers import CamembertConfig, CamembertModel

config = CamembertConfig()
model = CamembertModel(config)

# Le modèle est initialisé de façon aléatoire !

from transformers import CamembertModel

model = CamembertModel.from_pretrained("camembert-base")

model.save_pretrained("répertoire_sur_mon_ordinateur")

sequences = ["Hello!", "Cool.", "Nice!"]

from transformers import CamembertTokenizer

tokenizer = CamembertTokenizer.from_pretrained("camembert-base")
encoded_sequences = tokenizer(sequences)
encoded_sequences

import torch

model_inputs = torch.tensor(encoded_sequences)

output = model(model_inputs)

output