File size: 2,051 Bytes
78d1101 eda40b7 78d1101 4302c2b 78d1101 1c7cbff 78d1101 261a5aa 78d1101 f2b394c 78d1101 261a5aa ef4152c 261a5aa 065813f 261a5aa 4302c2b 065813f 885853c 4302c2b 261a5aa 5f4aaf1 261a5aa 9d520cc 261a5aa 20a6b7b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
import torch
import spaces
from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
from peft import PeftModel, PeftConfig
import os
import unicodedata
from huggingface_hub import login
max_length = 512
auth_token = os.getenv('HF_SPACE_TOKEN')
login(token=auth_token)
@spaces.GPU
def goai_traduction(text, src_lang, tgt_lang):
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
if src_lang == "fra_Latn" and tgt_lang == "mos_Latn":
model_id = "ArissBandoss/nllb-200-distilled-600M-finetuned-fr-to-mos-V4"
elif src_lang == "mos_Latn" and tgt_lang == "fra_Latn":
model_id = "ArissBandoss/mos2fr-3B-1200"
else:
model_id = "ArissBandoss/nllb-200-distilled-600M-finetuned-fr-to-mos-V4"
tokenizer = AutoTokenizer.from_pretrained(model_id, token=auth_token, truncation=True, max_length=512)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id, token=auth_token).to(device)
# Ajout du code de langue source
tokenizer.src_lang = src_lang
# Tokenisation du texte d'entrée
inputs = tokenizer(text, return_tensors="pt").to(device)
print(inputs)
# Utilisation de convert_tokens_to_ids au lieu de lang_code_to_id
tgt_lang_id = tokenizer.convert_tokens_to_ids(tgt_lang)
# Génération avec paramètres améliorés
outputs = model.generate(
**inputs,
forced_bos_token_id=tgt_lang_id,
max_new_tokens=1024,
min_length=10,
length_penalty=1.0,
early_stopping=False,
no_repeat_ngram_size=0 # Désactive la pénalité pour les répétitions
)
print("Token IDs:", outputs)
print("Tokens:", [tokenizer.decode([tok]) for tok in outputs[0]])
# Décodage de la sortie
translation = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
print("ici translation")
print(translation)
return translation
def real_time_traduction(input_text, src_lang, tgt_lang):
return goai_traduction(input_text, src_lang, tgt_lang) |