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# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
from flask import Flask, request
app = Flask(__name__)
app.config.from_pyfile('settings.py')
@app.route('/')
def index():
print(app.config["HUGGINGFACE_TOKEN"])
return "ISA Project Flask Server"
@app.post('/translate')
def translate():
article_en = request.form['original_text']
translate_code = request.form['translate_code']
access_token = app.config["HUGGINGFACE_TOKEN"]
tokenizer = AutoTokenizer.from_pretrained("SnypzZz/Llama2-13b-Language-translate", token="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")
model = AutoModelForSeq2SeqLM.from_pretrained("SnypzZz/Llama2-13b-Language-translate", token="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")
model_inputs = tokenizer(article_en, return_tensors="pt")
# translate from English
generated_tokens = model.generate(
**model_inputs,
forced_bos_token_id=tokenizer.lang_code_to_id[translate_code]
)
translated_sentence = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
return translated_sentence[0]
# English (en_XX),
# Spanish (es_XX),
# French (fr_XX),
# Japanese (ja_XX),
# Korean (ko_KR),
# Russian (ru_RU)
# Vietnamese (vi_VN),
# Chinese (zh_CN),
# Mongolian (mn_MN),
# Urdu (ur_PK)
if __name__ == "__main__":
app.run() |